15.2: Eukaryotic Pathogens - Biology

15.2: Eukaryotic Pathogens - Biology

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15.2: Eukaryotic Pathogens


A protist ( / ˈ p r oʊ t ɪ s t / ) is any eukaryotic organism (that is, an organism whose cells contain a cell nucleus) that is not an animal, plant, or fungus. While it is likely that protists share a common ancestor (the last eukaryotic common ancestor), [2] the exclusion of other eukaryotes means that protists do not form a natural group, or clade. [a] So some protists may be more closely related to animals, plants, or fungi than they are to other protists however, like algae, invertebrates, or protozoans, the grouping is used for convenience. The study of protists is termed protistology. [3]

Supergroups [1] and typical phyla

Many others
classification varies

The classification of a kingdom separate from animals and plants was first proposed by John Hogg in 1860 as the kingdom Protoctista in 1866 Ernst Haeckel also proposed a third kingdom Protista as "the kingdom of primitive forms". [4] Originally these also included prokaryotes, but with time these would be removed to a fourth kingdom Monera. [b] In the popular five-kingdom scheme proposed by Robert Whittaker in 1969, Protista was defined as eukaryotic "organisms which are unicellular or unicellular-colonial and which form no tissues", and the fifth kingdom Fungi was established. [5] [6] [c] In the five-kingdom system of Lynn Margulis, the term protist is reserved for microscopic organisms, while the more inclusive kingdom Protoctista (or protoctists) included certain large multicellular eukaryotes, such as kelp, red algae and slime molds. [9] Others use the term protist interchangeably with Margulis's protoctist, to encompass both single-celled and multicellular eukaryotes, including those that form specialized tissues but do not fit into any of the other traditional kingdoms. [10]

Besides their relatively simple levels of organization, protists do not necessarily have much in common. [11] When used, the term "protists" is now considered to mean a paraphyletic assemblage of similar-appearing but diverse taxa (biological groups) these taxa do not have an exclusive common ancestor beyond being composed of eukaryotes, and have different life cycles, trophic levels, modes of locomotion and cellular structures. [12] [13] Examples of protists include: [14] amoebas (including nucleariids and Foraminifera) choanaflagellates ciliates diatoms dinoflagellates Giardia Plasmodium (which causes malaria) oomycetes (including Phytophthora, the cause of the Great Famine of Ireland) and slime molds. These examples are unicellular, although oomycetes can form filaments, and slime molds can aggregate.

In cladistic systems (classifications based on common ancestry), there are no equivalents to the taxa Protista or Protoctista, as both terms refer to a paraphyletic group that spans the entire eukaryotic tree of life. In cladistic classification, the contents of Protista are mostly distributed among various supergroups: examples include the SAR supergroup (of stramenopiles or heterokonts, alveolates, and Rhizaria) Archaeplastida (or Plantae sensu lato) Excavata (which is mostly unicellular flagellates) and Opisthokonta (which commonly includes unicellular flagellates, but also animals and fungi). "Protista", "Protoctista", and "Protozoa" are therefore considered obsolete. However, the term "protist" continues to be used informally as a catch-all term for eukayotic organisms that are not within other traditional kingdoms. For example, the word "protist pathogen" may be used to denote any disease-causing organism that is not plant, animal, fungal, prokaryotic, viral, or subviral. [15]

Initiation of Transcription in Eukaryotes

Unlike the prokaryotic polymerase that can bind to a DNA template on its own, eukaryotes require several other proteins, called transcription factors, to first bind to the promoter region and then to help recruit the appropriate polymerase.

The Three Eukaryotic RNA Polymerases

The features of eukaryotic mRNA synthesis are markedly more complex than those of prokaryotes. Instead of a single polymerase comprising five subunits, the eukaryotes have three polymerases that are each made up of 10 subunits or more. Each eukaryotic polymerase also requires a distinct set of transcription factors to bring it to the DNA template.

RNA polymerase I is located in the nucleolus, a specialized nuclear substructure in which ribosomal RNA (rRNA) is transcribed, processed, and assembled into ribosomes ((Figure)). The rRNA molecules are considered structural RNAs because they have a cellular role but are not translated into protein. The rRNAs are components of the ribosome and are essential to the process of translation. RNA polymerase I synthesizes all of the rRNAs from the tandemly duplicated set of 18S, 5.8S, and 28S ribosomal genes. (Note that the “S” designation applies to “Svedberg” units, a nonadditive value that characterizes the speed at which a particle sediments during centrifugation.)

Locations, Products, and Sensitivities of the Three Eukaryotic RNA Polymerases
RNA Polymerase Cellular Compartment Product of Transcription α-Amanitin Sensitivity
I Nucleolus All rRNAs except 5S rRNA Insensitive
II Nucleus All protein-coding nuclear pre-mRNAs Extremely sensitive
III Nucleus 5S rRNA, tRNAs, and small nuclear RNAs Moderately sensitive

RNA polymerase II is located in the nucleus and synthesizes all protein-coding nuclear pre-mRNAs. Eukaryotic pre-mRNAs undergo extensive processing after transcription but before translation. For clarity, this module’s discussion of transcription and translation in eukaryotes will use the term “mRNAs” to describe only the mature, processed molecules that are ready to be translated. RNA polymerase II is responsible for transcribing the overwhelming majority of eukaryotic genes.

RNA polymerase III is also located in the nucleus. This polymerase transcribes a variety of structural RNAs that includes the 5S pre-rRNA, transfer pre-RNAs (pre-tRNAs), and small nuclear pre- RNAs . The tRNAs have a critical role in translation they serve as the “adaptor molecules” between the mRNA template and the growing polypeptide chain. Small nuclear RNAs have a variety of functions, including “splicing” pre-mRNAs and regulating transcription factors.

A scientist characterizing a new gene can determine which polymerase transcribes it by testing whether the gene is expressed in the presence of α-amanitin, an oligopeptide toxin produced by the fly agaric toadstool mushroom and other species of Amanita. Interestingly, the α-amanitin affects the three polymerases very differently ((Figure)). RNA polymerase I is completely insensitive to α-amanitin, meaning that the polymerase can transcribe DNA in vitro in the presence of this poison. RNA polymerase III is moderately sensitive to the toxin. In contrast, RNA polymerase II is extremely sensitive to α-amanitin. The toxin prevents the enzyme from progressing down the DNA, and thus inhibits transcription. Knowing the transcribing polymerase can provide clues as to the general function of the gene being studied. Because RNA polymerase II transcribes the vast majority of genes, we will focus on this polymerase in our subsequent discussions about eukaryotic transcription factors and promoters.

RNA Polymerase II Promoters and Transcription Factors

Eukaryotic promoters are much larger and more intricate than prokaryotic promoters. However, both have a sequence similar to the -10 sequence of prokaryotes. In eukaryotes, this sequence is called the TATA box, and has the consensus sequence TATAAA on the coding strand. It is located at -25 to -35 bases relative to the initiation (+1) site ((Figure)). This sequence is not identical to the E. coli -10 box, but it conserves the A–T rich element. The thermostability of A–T bonds is low and this helps the DNA template to locally unwind in preparation for transcription.

Instead of the simple σ factor that helps bind the prokaryotic RNA polymerase to its promoter, eukaryotes assemble a complex of transcription factors required to recruit RNA polymerase II to a protein coding gene. Transcription factors that bind to the promoter are called basal transcription factors. These basal factors are all called TFII (for Transcription Factor/polymerase II) plus an additional letter (A-J). The core complex is TFIID, which includes a TATA-binding protein (TBP). The other transcription factors systematically fall into place on the DNA template, with each one further stabilizing the pre-initiation complex and contributing to the recruitment of RNA polymerase II.

Strategies of Intracellular Pathogens for Obtaining Iron from the Environment

Most microorganisms are destroyed by the host tissues through processes that usually involve phagocytosis and lysosomal disruption. However, some organisms, called intracellular pathogens, are capable of avoiding destruction by growing inside macrophages or other cells. During infection with intracellular pathogenic microorganisms, the element iron is required by both the host cell and the pathogen that inhabits the host cell. This minireview focuses on how intracellular pathogens use multiple strategies to obtain nutritional iron from the intracellular environment in order to use this element for replication. Additionally, the implications of these mechanisms for iron acquisition in the pathogen-host relationship are discussed.

1. Introduction

Intracellular pathogens are organisms that are capable of growing and reproducing inside host cells. These pathogens can be divided into facultative intracellular parasites and obligate intracellular parasites [1]. Intracellular microorganisms are very important because they cause many human diseases, resulting in significant morbidity and mortality. Some examples of infectious diseases of global importance that are caused by intracellular microorganisms include tuberculosis, leprosy, typhoid, listeriosis, Legionnaire’s disease, malaria, leishmaniasis, Chagas’ disease, and toxoplasmosis. The course of infection is frequently long lasting and eventually results in chronic disease [2–4]. Facultative intracellular parasites, for example, bacteria such as Francisella tularensis, Listeria monocytogenes, Salmonella typhi, Mycobacterium spp., and Neisseria meningitidis, are capable of living and reproducing either inside or outside host cells. Obligate intracellular parasites cannot reproduce outside their host cell, which means that the parasite’s reproduction is entirely reliant on intracellular resources. Obligate intracellular parasites that infect humans include all viruses certain bacteria such as Chlamydia and Rickettsia certain protozoa such as Trypanosoma spp., Plasmodium, and Toxoplasma and fungi such as Pneumocystis jirovecii [3]. Facultative intracellular bacteria invade host cells when they can gain a selective advantage in the host. Bacteria that can enter and survive within eukaryotic cells are shielded from humoral antibodies and can be eliminated only by a cellular immune response [5]. Moreover, once inside host cells, bacteria must utilize specialized mechanisms to protect themselves from the harsh environment of the lysosomal enzymes encountered within the cells. Some examples include the bacterium Legionella pneumophila, which prefers the intracellular environment of macrophages for growth so it induces its own uptake and blocks lysosomal fusion by an undefined mechanism [6] Rickettsia, which destroys the phagosomal membranes (with which the lysosomes fuse) and Salmonella and Mycobacterium spp., which are resistant to intracellular killing by phagocytic and other cells [2]. Other facultative intracellular bacteria include enteroinvasive Escherichia coli, Listeria monocytogenes, Neisseria spp., and Shigella spp. [2, 7].

Obligate intracellular bacteria cannot live outside the host cell. Chlamydial cells are unable to carry out energy metabolism and lack many biosynthetic pathways and therefore are entirely dependent on the host cell to supply them with ATP (adenosine triphosphate) and other intermediate molecules [8]. Obligate intracellular bacteria cannot be grown in artificial media (agar plates/broths) in laboratories but require viable eukaryotic host cells (e.g., cell culture, embryonated eggs, and susceptible animals). Additional obligate intracellular bacteria include Coxiella burnetii, Rickettsia spp., and others [8, 9].

Microbial access to host nutrients is a fundamental aspect of infectious diseases. Pathogens face complex dynamic nutritional host microenvironments that change with increasing inflammation and local hypoxia. Because the host can actively limit microbial access to its nutrient supply, pathogens have evolved various metabolic adaptations to successfully exploit available host nutrients to facilitate their own proliferation [10]. Iron (Fe) is a key global regulator of cellular metabolism, which makes Fe acquisition a focal point of the biology of pathogen systems. In the host environment, the success or failure of Fe uptake processes impacts the outcome of pathogenesis [11]. After phagocytosis by macrophages, intracellular bacteria are located in a membrane-bound vacuole (phagosome), but the ensuing trafficking of this vacuole and subsequent bacterial survival strategies vary considerably. If the ingested bacteria have no intracellular survival mechanisms, the bacteria-containing phagosomes fuse with the lysosomal compartment, and bacteria are digested within 15–30 min. For this reason, the majority of intracellular bacteria and other parasites must keep host cells alive as long as possible while they are reproducing and growing [7, 9]. To grow, intracellular pathogens need nutrients such as the iron, that might be scarce in the cell, because this is usually retained or stored by proteins.

Pathogens that infect macrophages require Fe for growth, but, during infection, Fe is required by both the host cell and the pathogen that inhabits the host cell [12]. Macrophages require Fe as a cofactor for the execution of important antimicrobial effector mechanisms, including the NADPH- (nicotinamide adenine dinucleotide phosphate-oxidase-) dependent oxidative burst and the production of nitrogen radicals catalyzed by the inducible nitric oxide synthase [13]. On the other hand, intracellular bacteria such as Legionella pneumophila, Coxiella burnetii, Salmonella typhimurium, and Mycobacterium tuberculosis have an obligate requirement for Fe to support their growth and survival inside host cells [14]. In fact, it has been documented that deprivation of Fe in vivo and in vitro severely reduces the pathogenicity of M. tuberculosis, C. burnetii, L. pneumophila, and S. typhimurium [13–15].

2. Iron in the Human Host

Iron (Fe) is essential for the growth of all organisms. The human body contains 3–5 g of Fe distributed throughout the body in the protein hemoglobin, tissues, muscles, bone marrow, blood proteins, enzymes, ferritin, hemosiderin, and transport in plasma. Iron (approximately 75%) is contained in the protein hemoglobin (Hb) and in other iron-bound proteins that are important for cellular processes, and whatever remains in plasma (approximately 25%) is bound to plasma proteins such as transferrin (Tf) [16].

Dietary Fe has two main forms: heme and nonheme. Plants and iron-fortified foods contain nonheme Fe only, whereas meat, seafood, and poultry contain both heme and nonheme iron. Heme iron, which is formed when Fe combines with protoporphyrin IX, contributes about 10% to 15% of total Fe intakes in western populations [17]. Intestinal absorption is the primary mechanism regulating Fe concentrations in the body. Once ingested, Fe absorption occurs predominantly in the duodenum and upper jejunum. The mechanism of iron transport from the gut into the blood stream remains unknown. The first step of the pathway of iron absorption in the human host involves reduction of ferric Fe 3+ to Fe 2+ in the intestinal lumen by reductases or cytochrome b and transport of Fe 2+ across the duodenal epithelium by the apical transporter DMT1 (divalent metal transporter). In nonintestinal cells most Fe uptake occurs via either the classical clathrin-coated pathway utilizing transferrin receptors or the poorly defined transferrin receptor independent pathway. Tf is the principal Fe storage protein that stores and releases Fe inside cells that express the transferrin receptor (TfR). The delivery of Fe from Tf is mediated by an acidic pH 5.5 of the endocytic vesicles carrying holo-Tf and TfR complexes. Fe is then transported across the endosomal membrane and utilized. Excess intracellular Fe is sequestered into the protein Ft [18, 19].

In a healthy individual Fe is largely intracellular, sequestered within Ft or as a cofactor of heme complexed to Hb within erythrocytes. Any extracellular free Fe is rapidly bound by circulating Tf. Hb or heme that is released as a result of natural erythrocyte lysis is captured by haptoglobin and hemopexin, respectively. Taken together, these factors ensure that vertebrate tissue is virtually devoid of free iron [21]. Maintaining cellular Fe content requires precise mechanisms for regulating its uptake, storage, and export. The iron response elements or iron-responsive elements (IRP1 and IRP2) are the principal regulators of cellular Fe homeostasis in vertebrates. IRPs are cytosolic proteins that bind to Fe-responsive elements (IREs) in the 5′ or 3′ untranslated regions of mRNAs encoding proteins involved in Fe uptake (TfR1, DMT1), sequestration (H-ferritin subunit (FTH1) and L-ferritin subunit (FTL)), and export (ferroportin). When cells are Fe deficient, IRPs bind to 5′ IREs in ferritin and ferroportin mRNAs with high affinity to repress translation and to 3′ IREs in TfR1 mRNA to block its degradation (Tf is involved in the transport or Fe). When Fe is in excess, IRPs do not bind to IREs, increasing synthesis of Ft and ferroportin (proteins involved in the storage of Fe), while promoting the degradation of TfR1 mRNA. The coordinated regulation of Fe uptake, storage, and export by the IRPs ensures that cells acquire adequate Fe for their needs without reaching toxic levels [22].

The ability of pathogens to obtain Fe from Tf, Lf, Ft, Hb, and other iron-containing proteins of their host is central to whether they live or die [14]. This is because these proteins are the main Fe sources for intracellular pathogens in the macrophage. Iron homeostasis in the macrophage is determined by uptake processes through Lf, Tf, DMT-1, and phagocytosis of senescent erythrocytes as well as by export through ferroportin (Fpn), as we have discussed before. Inside infected macrophages, a pathogen’s access to Fe may be limited by natural resistance-associated macrophage protein 1 (SLC11A1, formerly Nramp1). SLC11A1 is a divalent metal transporter, recruited to the late endosomal and phagosomal membrane of macrophages and other professional phagocytes. Although SLC11A1 contributes to macrophages’ efficiency in the recycling of erythrocyte-derived Fe, the main function of SLC11A1 seems to be the protection against microbes [20]. Its gene is present in inbred strains of mice in two allelic forms that determine the resistance or susceptibility to several intracellular pathogens such as Mycobacterium spp., Salmonella spp., and Leishmania spp. [23]. Some groups of researchers have suggested that Fe is transported via this protein into the pathogen-containing phagosome, causing the death of the pathogen by catalyzing the formation of reactive oxygen species (ROS), while others argue for Fe efflux from the phagosome, restricting pathogenic growth by Fe deprivation [23, 24]. Another Fe transporter that is expressed in macrophages is Fpn. This transporter is present in the macrophage cytoplasmic membrane and is responsible for Fe export. Overexpression of Fpn has been reported to inhibit the intramacrophagic growth of M. tuberculosis and Salmonella enterica, presumably through Fe deprivation. The details of this mechanism are unclear [25, 26]. A scheme of Fe sources in the human body and iron homeostasis inside the macrophage is shown in Figure 1.

3. Mechanisms Used by Intracellular Pathogens for Obtaining Iron: A General Point of View

During infection, pathogens are capable of altering the battlefield to increase the abundance of potential Fe sources. For example, bacterial cytotoxins damage host cells, leading to the release of Ft, while hemolytic toxins from bacteria can lyse erythrocytes, liberating Hb. The resulting inflammatory response includes the release of Lf from secondary granules contained with polymorphonuclear leukocytes (PMNs) [10, 21, 27]. Pathogens are capable of exploiting these diverse Fe sources through the elaboration of a variety of Fe acquisition systems. In the case of extracellular pathogens, they can acquire Fe through receptor-mediated recognition of Tf, Lf, hemopexin, hemoglobin, or hemoglobin-haptoglobin complexes [19, 27]. Alternatively, secreted siderophores can remove Fe from Tf, Lf, or Ft, whereupon siderophore-iron complexes are recognized by cognate receptors at the bacterial surface. Siderophores are small ferric iron chelators that bind with extremely high affinity (iron formation constants

range from 10−20 to 10−50 M), some of which can extract iron from Tf and Lf [21]. Analogously, secreted hemophores can remove heme from Hb or hemopexin and deliver heme to bacterial cells through binding with hemophore receptors. Siderophore mediated Fe acquisition is inhibited by the innate immune protein siderocalin, which binds siderophores and prevents receptor recognition. This host defense is circumvented through the production of stealth siderophores that are modified in such a way as to prevent siderocalin binding [21, 27].

For proper use of Fe, extracellular or intracellular parasites must possess at least the following systems: (a) Fe sensors for monitoring Fe concentration in the intracellular environment, (b) synthesis and release of high-affinity compounds that can compete with host Fe binding proteins for Fe acquisition and storage, or proteases to degrade these host Fe binding proteins, (c) transportation of these Fe-loaded molecules and their assimilation, and (d) regulation of the expression of proteins involved in iron metabolism, in order to maintain iron homoeostasis [27, 28]. Once ingested by macrophages, many intracellular parasites are taken up by phagosomes through endocytosis. Thus, the success of intracellular parasites seems to be related mainly to their ability to take up Fe from the proteins Tf, Hb, hemoglobin-haptoglobin, free heme, and Ft. Figure 2 shows intracellular parasites and Fe sources inside a macrophage.

In order to take the Fe from Tf, these systems can be divided into three main categories: siderophore-based systems, heme acquisition systems, and transferrin/lactoferrin receptors.

Upon removing Fe from host proteins, iron-loaded siderophores are bound by cognate receptors expressed at the bacterial surface. The siderophore-iron complex is then internalized into the bacterium and the Fe is released for use as a nutrient source [21]. Heme acquisition systems typically involve surface receptors that recognize either heme or heme bound to hemoproteins such as hemoglobin or hemopexin. Heme is then removed from hemoproteins and transported through the envelope of bacteria into the cytoplasm. Once inside the cytoplasm, the iron is released from heme through the action of heme oxygenases or reverse ferrochelatase activity. Bacterial pathogens can also elaborate secreted heme-scavenging molecules that remove heme from host hemoproteins. These molecules, known as hemophores, are functionally analogous to siderophores but are proteins that target heme, whereas siderophores are small molecules that target iron atoms [29]. In addition to acquiring Fe from Tf and Lf through siderophore-based mechanisms, some pathogens are capable of direct recognition of these host proteins through receptors [21]. These receptors are modeled to recognize Tf or Lf, leading to Fe removal and subsequent transport into the bacterial cytoplasm. Additionally, acidification of the phagosome permits Fe release from Tf and probably Lf and, in this way, some pathogens can gain access to this element directly [19, 21, 30].

The following sections summarize the Fe acquisition systems used by some intracellular pathogens. Table 1 shows Fe sources, mechanism of uptake, transport and regulation, used by intracellular parasites.

4. Mechanism of Intracellular Pathogens for Obtaining Iron from Host Sources

4.1. Francisella tularensis

F. tularensis, the bacterial cause of tularemia, is a virulent intracellular pathogen that can replicate in multiple cell types. Acidification of the phagosome and acquisition of Fe is essential for growth of F. tularensis [31]. An acidic pH promotes the release of Fe from host cell Tf. To acquire the Fe from Tf, F. tularensis involves a receptor for this protein (Transferrin receptor 1, TfR1), induction of ferrireductases, an iron membrane transporter (DMT-1), and iron regulatory proteins (IRP1 and IRP2) this is an active Fe acquisition system associated with a sustained increase of the labile Fe pool inside the macrophage [31]. In addition, F. tularensis uses high-affinity transportation of ferrous Fe across the outer membrane via the proteins FupA and FslE. FsIe appears to be involved in siderophore-mediated ferric Fe uptake, whereas FupA facilitates high-affinity ferrous Fe uptake [32]. It has been hypothesized that F. tularensis uses the Fe from Lf to sustain its growth however, the mechanism of Fe acquisition from LF remains undetermined [33]. It is most likely that F. tularensis can infect many types of cells because it contains several strategies for Fe acquisition. It has been reported that the expression of certain F. tularensis virulence genes is clearly regulated by Fe availability [34].

The expression of TfR1 is critical for the intracellular proliferation of Francisella. This contrasts with infection of macrophages by Salmonella typhimurium, which does not require expression of TfR1 for successful intracellular survival. Macrophages infected with Salmonella lack significant induction of DMT-1, Steap3, and IRP1 and maintain their labile Fe pool at normal levels [12]. Authors argue that this might be explained by Salmonella’s intracellular localization within an endosomal structure or perhaps by more efficient Fe acquisition strategies compared to Francisella [12].

4.2. Salmonella spp.

Salmonella typhimurium is an invasive pathogen that causes diseases ranging from mild gastroenteritis to enteric fever. To establish a systemic infection, Salmonella spp. must invade the epithelial wall of the intestine before the bacteria are ingested by immune effector cells and transported to lymph nodes, the spleen, and other organs. Salmonella spp. reside within modified phagosomes in macrophages, where replication is promoted and killing is evaded. Fe is an essential micronutrient for replication, and Salmonella spp. harbor various Fe acquisition systems, such as the siderophores enterobactin and salmochelin [35]. As iron sources, Salmonella spp. use Fe 2+ , Fe 3+ , heme, ovotransferrin, and Tf [35, 36]. S. Typhimurium acquires Fe 2+ from hemophagocytic macrophages and also secretes siderophores via IroC and EntS to bind Fe 3+ , which is subsequently taken up by outer membrane receptors including IronN and FepA. ABC transporters such as FepBCDG are responsible for the transport of siderophores through the cytoplasmic membrane, whereas molecular iron is taken up via Feo-mediated transmembrane transport [35, 36].

During the infection process in vivo, S. typhimurium induces a number of virulence genes that are required to circumvent host defenses and/or acquire nutrients from the host. A putative Fe transporter in Salmonella called Pathogenicity Island 1, or sitABCD, has been characterized. The sitABCD operon is induced under Fe-deficient conditions in vitro and is repressed by Fur (ferric uptake regulator). This locus is specifically induced in animal models after invasion of the intestinal epithelium, suggesting that SitABCD plays an important role in Fe acquisition in the animal. To regulate its Fe content, Salmonella enterica serovar Typhimurium possesses four ferritins: bacterioferritin (Bfr), ferritin A (FtnA), ferritin B (FtnB), and Dps. The heme-containing Bfr accounts for the majority of stored Fe, followed by FtnA. Inactivation of Bfr elevates the free intracellular Fe concentration and enhances susceptibility to H2O2 stress. The DNA-binding Dps protein provides protection from oxidative damage without affecting the free intracellular Fe concentration at steady state. FtnB appears to be particularly important for the repair of Fe-sulfur clusters of aconitase that undergo oxidative damage, and, in contrast to Bfr and FtnA, is required for Salmonella virulence in mice. Moreover, FtnB and Dps are repressed by the Fe-responsive regulator Fur and induced under conditions of Fe limitation, whereas Bfr and FtnA are maximally expressed when Fe is abundant. The absence of a conserved ferroxidase domain and the potentiation of oxidative stress by FtnB in some strains that lack Dps suggest that FtnB serves as a facile cellular reservoir of Fe 2+ [37].

4.3. Chlamydia spp.

Chlamydia is an infection that is caused by the bacteria Chlamydia trachomatis. It is the most common sexually transmitted disease in the U.S., with nearly 3 million cases reported each year (the actual number of cases is likely much higher). The developmental cycle of C. trachomatis includes two forms: an infectious elementary body (EB) and a reticulate body that multiplies within the inclusion by binary fission. A third developmental form is the persistent form, which exists as a mechanism of survival under stressful conditions. Persistence is induced in response to changes in the culture medium, including amino acid or Fe deprivation, and in the presence of antibiotics or cytokines such as gamma interferon (IFN) [38]. It has been shown that Fe is an essential factor in the growth and survival of C. trachomatis and C. pneumoniae (this bacterium causes pneumonia) [39]. Although homologues for bacterial siderophores are missing in the genome of this bacterium, TfR expression does occur. C. trachomatis also appears to be missing a tonB analogue, which would span the periplasm and is crucial in energy transfer to substrate-specific outer membrane transporters that are used to bring Fe-siderophore complexes to the cell. Considering these apparent gaps in the genome, one could speculate that the C. trachomatis genome would need a reductase on the inclusion membrane to transport Fe 2+ from the eukaryotic cytosol into the inclusion. C. trachomatis and C. pneumoniae appear to use the host’s Fe transport pathways by attracting TfR and Ft to the phagosome [39]. A report from Vardhan et al. (2009) showed that C. trachomatis alters the Fe-regulatory protein-1 (IRP-1) binding capacity and modulates cellular iron homeostasis in HeLa-229 cells, suggesting that Fe homeostasis is modulated in CT-infected HeLa cells at the interface of acquisition and commensal use of Fe [40].

ATP-binding cassette (ABC) transport systems play a role in the acquisition of Fe and Fe-complexes, amino acids, sugars, and other compounds. They consist of a soluble periplasmic protein that binds the targeted molecule and changes conformation to close around the substrate. The periplasmic binding protein moves to and binds the transmembrane protein permease in receptor-ligand mechanisms. An ATP-binding lipoprotein binds to the ATP, creating a conformational change in the permease complex that transports the substrate into the cytoplasm. In other pathogenic bacteria, ABC transport systems that transport Fe, zinc, and manganese into the cytoplasm include Tro from Treponema pallidum, Yfe from Yersinia pestis, and Fbp from Neisseria meningitidis [40]. There is evidence that YtgA secretion occurs in C. trachomatis, and YtgA does have high homology with periplasmic binding proteins of the ABC transport systems. ytaA is a gene of 978 bp that resides in an operon with ytgBVD. YtgB and Ytg have predictable membrane-spanning domains and most likely form the pore of the ABC transporter. YtgA contains similar metal-binding motifs (e.g., histidine, tyrosine) to other metal-binding periplasmic proteins, suggesting a role for YtgA as an Fe-binding periplasmic protein, in addition to its location on the chlamydial membrane [41].

4.4. Neisseria spp.

Acquisition of Fe and Fe-complexes has long been recognized as a major determinant in the pathogenesis of Neisseria spp., and some of their high-affinity iron uptake systems are important virulence factors in bacteria. These have been shown to play a major role in promoting the survival of the meningococcus within the host. Most species are Gram-negative bacteria that are primarily commensal inhabitants or reside in the mucus membranes of mammals. There are 12 Neisseria species of human origin, with N. meningitidis and N. gonorrhoeae being important opportunistic pathogens. These intracellular pathogens contain high-affinity iron uptake systems, which allow meningococci to utilize the human host proteins Tf, Lf, Hb, and haptoglobin-hemoglobin as sources of essential Fe [29, 42]. Although the meningococci do not produce siderophores, studies indicate that meningococci may be able to use heterologous siderophores secreted by other bacteria. For some time, it has been reported that the gonococci could utilize ferric enterobactin, enterobactin derivatives, aerobactin, and salmochelin S2 in a FetA- and TonB-dependent manner [29]. In N. gonorrhoeae, an outer membrane protein named FetA (formerly FrpB) was recently described. FetA is an outer membrane transporter and is part of an iron-regulated operon that encodes a periplasmic binding protein and the components of a putative ABC transport system. FetA has demonstrated low binding affinity and the transport of ferric enterobactin. The binding contact of FetA for enterobactin was much lower than that for other enterobactin receptors, and it was therefore proposed that this receptor could interact with high affinity to an as-yet unidentified phenolate siderophore. A homologous protein, with 91% similarity to gonococcal FetA, has been identified in N. meningitidis and presumably functions in a similar manner [30, 43]. Only fetA and not the downstream genes require an iron-regulator MpeR for regulation. MpeR regulation is important because it may aid in gonococcal immune evasion. MpeR was suggested to modulate any change in mtrF expression that is needed for full hydrophobic agent resistance. AraC-like regulators of N. meningitidis are homologues of the N. gonorrhoeae type MpeR that is specific to the pathogenic Neisseria species. Both are induced during Fe limitation, and this regulation is also mediated by the Fur regulator. The presence of MpeR in a regulatory cascade downstream of the Fur master Fe regulator suggests that it is being expressed in the Fe limiting environment of the host, where it may in turn regulate a group of genes, including the divergent Fe transport locus, in response to signals that are important for infection [44].

Two proteins, transferrin-binding protein A (TbpA) and transferrin-binding protein B (TbpB), function as the transferrin receptor in N. meningitidis. TbpA and TbpB are induced along with several other proteins in the outer membranes of N. meningitidis under Fe-restricted conditions [30]. Initially, an affinity isolation procedure using biotinylated transferrin was employed to demonstrate the presence of two transferrin-binding proteins in N. meningitidis. The proteins that bound transferrin were TbpA (formerly Tbp1), which is 98 kDa, and TbpB (formerly Tbp2), which is 68 kDa [45]. Among different meningococcal isolates, the molecular masses of TbpA and TbpB vary, with TbpA ranging from 93 to 98 kDa and the more heterogenetic TbpB varying from 68 to 85 kDa. TbpA can be found in all strains. Although it has not been characterized as well as the Tf receptor, the Lf receptor is believed to be an important meningococcal virulence factor [29]. The Lf receptor of N. meningitidis, like the Tf receptor, consists of two protein components, LbpA and LbpB. Initial experiments using affinity isolation by Lf identified a 98-kDa lactoferrin-binding protein named LbpA, formerly known as IroA [46].

4.5. Legionella pneumophila

Legionella pneumophila, the causative agent of Legionnaire’s disease, is a facultative intracellular parasite of human macrophages and freshwater amoebae. This pathogenic bacterium is commonly found in water, thereby presenting a risk that it could be transmitted to humans via inhalation of contaminated aerosols. L. pneumophila resides in the phagosome, although this phagosome does not fuse with endosomes and lysosomes and is at nearly neutral pH during the early stages of the intracellular life cycle. It appears to fuse with low-pH cellular compartments during the later stages of the infection [47].

The ability of L. pneumophila to acquire host cell Fe is pivotal for the parasite to establish a successful intracellular infection. To occupy its intracellular niche, this pathogen has developed multiple Fe acquisition mechanisms: the ira AB locus, which encodes a transporter for Fe-loaded peptides the cytochrome c maturation ccm genes the Fe-regulated frgA, whose product is homologous to aerobactin synthetases legiobactin siderophores and two internal ferric reductases. Robey and Cianciotto (2002) identified and characterized L. pneumophila Feo AB, which bears homology to E. coli and Salmonella enterica serovar Typhimurium FeoAB. In those bacteria, FeoB has been shown to be a ferrous Fe transporter and FeoA is possibly involved in Fe 2+ uptake [48].

In 2014, Portier and Cols discovered gene ipp_2867, which was highly induced in Fe-restricted conditions. A sequence analysis predicts that Lpp_2867 is a membrane protein involved directly or indirectly in Fe 2+ transport and is also a virulence factor [49].

4.6. Shigella spp.

Shigella is a Gram-negative bacterium of the Enterobacteriaceae family and is the etiological agent of bacillary dysentery or shigellosis. Shigella encompasses four subgroups (S. flexneri, S. sonnei, S. dysenteriae, and S. boydii), and all species are able to grow in a variety of environments, including intracellularly in host epithelial cells. Shigella has a number of different Fe transport systems that contribute to the bacterium’s ability to grow in these diverse environments [50]. Siderophore Fe uptake systems, heme transporters, and Fe 3+ and Fe 2+ transport systems are present in these bacteria, and the genes encoding some of these systems appear to have spread among the Shigella species by horizontal transmission [50, 51]. Fe is not only essential for the growth of Shigella but also plays an important role in the regulation of metabolic processes and virulence determinants in Shigella. This regulation is mediated by the repressor protein Fur and the small RNA RyhB [52]. The only Fe transport system that appears to be common to all members of the E. coli/Shigella group is Feo. Shigella spp. have transport systems for both ferric and ferrous iron. The Fe can be taken up as free Fe or complexed with a variety of carriers. All Shigella species have both the Feo and Sit systems for acquisition of Fe 2+ , and all have at least one siderophore-mediated system for transport of Fe 3+ [53]. Several of the transport systems, including Sit, Iuc/IutA (aerobactin synthesis and transport), Fec (ferric di-citrate uptake), and Shu (heme transport), are encoded within pathogenicity islands. The presence and the genomic locations of these islands vary considerably among the Shigella species and even between isolates of the same species [53, 54]. The expression of the Fe transport systems is influenced by the concentration of Fe and by environmental conditions, including the level of oxygen. ArcA and FNR regulate Fe transport gene expression as a function of oxygen tension, with the sit and iuc promoters being highly expressed in aerobic conditions, while the feo Fe 2+ transporter promoter is most active under anaerobic conditions [52]. The effects of oxygen are also observed in infection of cultured cells by S. flexneri the Sit and Iuc systems support plaque formation under aerobic conditions, whereas Feo allows plaque formation to occur anaerobically [52, 53].

4.7. Listeria monocytogenes

L. monocytogenes is a Gram-positive, intracellular pathogen responsible for the fatal disease listeriosis. L. monocytogenes is recognized as a significant public health problem. The ability of this bacterium to acquire and utilize Fe is not only essential during infection but can also support its growth and survival in many diverse environmental niches.

L. monocytogenes possesses at least 4 mechanisms that enable Fe uptake: (1) acquisition of protein-bound Fe that involves the HupDGC protein (for the uptake of hemin, hemoglobin), or Fhu protein (involved in the uptake of ferrichrome siderophores) inside the cell, then Fe can be bound to the Fri protein (ferritin-like) Fur regulated (2) extracellular and/or surface-bound Fe reductases (3) a citrate inducible ferric citrate uptake system and (4) siderophore and siderophore-like systems [55].

The Listeria life cycle involves escape from the phagosome, which is considered to be Fe-limiting and permits proliferation in the host-cell cytosol, where Fe-saturated Ft is stored. It has been hypothesized that L. monocytogenes has access to Fe through increased expression of the PrfA-regulated virulence factors listeriolysin (LLO) and ActA, which are used for phagosomal escape. Increased Fe concentrations result in the upregulation of internalin proteins InlA and InlB, which are required for invasion [56].

Fe homeostasis in Listeria is controlled by the regulatory protein Fur. It has been shown that expression of Fur is negatively regulated by PerR, a Fur homologue that is involved in the oxidative stress response. Fourteen Fur-regulated genes have been identified in L. monocytogenes, including genes that encode Fe 2+ transporters and ferrichrome ABC transporters and proteins involved in Fe storage [56, 57].

4.8. Coxiella burnetii

Coxiella burnetii is the causative bacterial agent of Q fever in humans and is one of the most infectious pathogens known. Human infection with C. burnetii is generally a zoonosis that is acquired by inhalation of contaminated aerosols. Q fever typically presents as an acute, self-limiting flu-like illness accompanied by pneumonia or hepatitis. In 1% of cases, a severe chronic infection can occur, in which endocarditis is the predominant manifestation [58]. It is essential for most pathogenic bacteria to overcome the limitation of Fe in the intracellular host. To overcome this limitation, bacteria maintain cell storage systems under the tight control of Fur. It has been suggested that it is an absolute requirement for C. burnetii, similar to L. pneumophila, to regulate Fe assimilation via the Fur regulon. One study revealed that the Fur-regulon in C. burnetii consists of a Fur-like protein (CBU1766) and the putative iron-binding protein Frg1 (CBU0970) [59].

Iron plays a rather limited role in the pathogenesis of C. burnetii. Reports have described the expression of a thiol-specific peroxidase (CBU0963) in C. burnetii that belongs to the atypical 2-cysteine subfamily of peroxiredoxins, also designated as bacterioferritin comigratory proteins (BCPs). The implication is that this protein might protect DNA from the Fenton reaction [60]. Comparison to L. pneumophila, a phylogenetic relative, revealed that C. burnetii rarely encodes any known Fe acquisition or storage proteins, aside from some Fe dependent pathways, as well as the heme biosynthesis pathway and proteins such as SodB.

4.9. Mycobacterium spp.

Mycobacterium is a genus of Actinobacteria, given its own family, the Mycobacteriaceae. The genus includes pathogens known to cause serious diseases in mammals, including tuberculosis (Mycobacterium tuberculosis) and leprosy (Mycobacterium leprae). Similar to most microorganisms, Mycobacterium tuberculosis, the causative agent of tuberculosis, requires Fe for essential metabolic pathways. Like several other pathogenic bacteria, it has evolved an intricate mechanism of acquiring, assimilating, and storing Fe, which is a component that determines the fate of the pathogen inside the host [28]. Because Fe is not freely available in the host, Mycobacteria must actively compete for this metal to establish an infection, but they must also carefully control Fe acquisition, as excess free Fe can be extremely toxic. The molecules responsible for Fe acquisition in mycobacteria include simple molecules such as salicylic acid and citric acid, apart from the two classes of siderophores.

To acquire Fe, mycobacteria produce siderophores (high-affinity Fe chelators). The lipophilic siderophores that remain associated with the cell wall are called mycobactins, and the second class of siderophores includes polar forms that are released into the extracellular medium [28]. These are called carboxymycobactins (released by pathogenic mycobacteria) and exochelins (released by nonpathogenic mycobacteria). M. tuberculosis and M. smegmatis produce salicylate-containing siderophores known as mycobactins. There are two forms of mycobactins: carboxymycobactin, which is a water-soluble secreted molecule, and the cell-associated mycobactin, which is a hydrophobic molecule that is retained on the cell surface. In addition to mycobactins, M. smegmatis also produces a peptidic siderophore known as exochelin, which is the predominant siderophore secreted by this mycobacterium under Fe limitation [28].

The identification of two genes that are annotated as fecB and fecB2 and that code proteins similar to FecB of Escherichia coli suggests that M. tuberculosis may also utilize ferric dicitrate as an Fe source [61]. Siderophores avidly bind Fe +3 and can effectively compete with host Fe binding proteins for this metal. Fe +3 -carboxymycobactin can transfer Fe +3 to mycobactin or bring it into the cell via the iron-regulated transporter IrtAB. The putative transporter encoded by fxuABC may transport Fe +3 -exochelin complexes.

Previous work has linked the ESX-3 system with the ability of mycobacteria to adapt to Fe limitation. ESX-3 is one of the five type VII secretion systems encoded by the M. tuberculosis genome. Studies that examined an M. smegmatis exochelin synthesis mutant indicated an ESX-3 requirement for Fe +3 -mycobactin utilization. The precise role of ESX-3 in Fe acquisition in M. tuberculosis is unknown, but it is clear that ESX-3 is necessary for adaptation to low Fe conditions [62]. On the other hand, it has been documented that M. tuberculosis increases microvesicles production in response to Fe restriction and that these microvesicles contain mycobactin, which can serve as an iron donor and supports replication of Fe-starved mycobacteria. Consequently, the results revealed that microvesicles play a role in Fe acquisition in M. tuberculosis, and this can be critical for survival in the host. Recent studies have demonstrated that failure to assemble the Fe acquisition machinery or to repress Fe uptake has deleterious effects for M. tuberculosis [28].

A protein that was speculated to be a mycobacterial iron transporter is the Mramp, and this protein was able to increase the uptake of Fe 2+ and Zn 2+ in a pH dependent manner. Mramp was expected to be a cation transporter with no selective transport of Fe, although additional reports indicate that Mramp may act as a cation efflux pump [63].

Bacterioferritin-like molecules bfrA (a putative bacterioferritin) and bfrB (an Ft-like protein) have been identified in the M. tuberculosis genome and are the principal Fe storage molecules. Their expression is induced under Fe-rich conditions and repressed under Fe-deprived conditions. Therefore, it is speculated that this format allows the maintenance of basal levels of bacterioferritin inside the pathogen so that any amount of excess Fe can be immediately stored in a bound form [64]. Regulation of gene expression in M. tuberculosis includes that of regulatory proteins, stress response proteins, enzymes, and PE-PGR/PPE proteins. The genes that are upregulated under Fe-deprived conditions included those that are responsible for acquisition of Fe, such as siderophores, biosynthesis gene clusters mbt1 and mbt2, and Fe regulated transporters of siderophores irtA, irtB, Rv2895c, and esx [28]. Genes that are upregulated under Fe-rich conditions include bacterioferritin and ferritin (bfrA and bfrB), as they serve to store excess Fe as catalase-peroxidase, or katG and its regulator, ferric uptake regulator A (FurA) [63].

There are two Fur proteins, FurA and FurB. After binding ferric iron, FurA recognizes and binds to a 19-base-pair pseudopalindrome sequence of a specific DNA motif called Fur Box that is present upstream to a gene and acts as a repressor. FurB, on the other hand, was later found to be regulated by zinc and not Fe and has been correctly referred to as Zur.

IdeR, an Fe-dependent repressor and activator, is the major regulatory protein involved in homeostasis in mycobacteria. Belonging to the Diphtheria toxin repressor family (DtxR), it acts as a homodimer, with each monomer possessing two binding sites for Fe. Two homodimers with four bound Fe ions recognize a 19-base-pair palindromic sequence and in Fe-replete conditions and negatively regulate the expression of proteins required in Fe-depleted conditions [65]. The genes or gene clusters essentially required during Fe starvation are effectively repressed by IeR. These include the siderophore synthesis gene cluster, mbt1, mbt2, irtA, irtB, and Rv2895c. Therefore, there are certain proteins that are differentially regulated by Fe in an IdeR-independent fashion. These include lipoprotein IprE, KatG, 50S ribosomal protein, L22, and ATP synthase c chain, two component response regulators, MTrA, PE-PGRS proteins, and NifU-like proteins [28]. Fur and Fe-dependent repressors and activators or IdeR are the two key proteins that regulate expression of other Fe-dependent genes [28, 63].

4.10. Candida spp.

Candida is a genus of yeast and is the most common cause of fungal infection worldwide [66, 67]. Many Candida species are harmless commensals or endosymbionts of hosts including humans however, when mucosal barriers are disrupted or the immune system is compromised they can invade tissues and cause disease [66]. Among Candida species, C. albicans is responsible for the majority of Candida bloodstream and mucosal infections. However, in recent years, there is an increasing incidence of infections caused by C. glabrata and C. rugosa, C. parapsilosis, C. tropicalis, and C. dubliniensis [66]. Varied virulence factors and growing resistance to antifungal agents have contributed to their pathogenicity [66, 68].

Candida albicans can cause infections (candidiasis or thrush) in humans and other animals. Between the commensal and pathogenic lifestyles, this microorganism inhabits host niches that differ markedly in the levels of bioavailable iron. Once introduced into the bloodstream, C. albicans can acquire Fe from the molecules that are used by the host to sequester this metal [69]. For example, several groups have identified C. albicans hemolytic activity capable of releasing Hb from host erythrocytes. Free Hb or its heme/hemin metal-porphyrin ring is bound by a hemoglobin receptor, Rbt5, on the fungal cell surface, followed by endocytosis of Rbt5-hemoglobin complexes and release of Fe 2+ by the heme oxidase, Hmx1 [69]. It has been reported that C. albicans encodes four additional homologs of Rbt5, of which Rbt51 has also been demonstrated to bind to hemin [69].

C. albicans can also utilize host Tf in vitro as a sole source of Fe, probably through the involvement of a transferrin receptor, similar to certain bacterial pathogens. It has been reported that the Fe 3+ derived from Tf is taken up by a reductive iron uptake system that is conserved with the well-described high affinity iron uptake system of Saccharomyces cerevisiae. Fe 3+ is first reduced to soluble Fe 2+ by a cell surface-associated ferric reductase [69]. In coupled reactions, Fe 2+ is then oxidized and imported into the fungal cytoplasm by a multicopper ferroxidase/iron permease complex. C. albicans encodes 17 putative ferric reductases, five putative multicopper ferroxidases, and four putative ferric permeases with potential functions in reductive Fe uptake, and different subsets of these enzymes are expressed under different in vitro conditions. Of the two ferric permeases, only Ftr1 is expressed when iron is limited, and FTR1 is essential in a murine bloodstream infection model of virulence [69].

In tissues, the Fe is mainly bound to Ft. The Ft is found inside of macrophages and epithelial cells. This protein binds 4500 Fe atoms, and cytoplasmic iron-ferritin complexes are generally extremely stable. It has been documented that C. albicans utilizes Ft as Fe source in vitro, or directly from epithelial cells in culture. When this yeast was cocultured with a human oral epithelial cell line, the protein Ft was found bound onto their surface. This Ft binding protein denominated Als3, is located in the hyphae from C. albicans [69]. Als3 also plays important roles in C. albicans biofilm formation [70] and adhesion to host epithelial and endothelial cells and induced endocytosis of hyphae [71]. Thus, Als3 integrates Fe uptake and virulence functions but only in oral epithelial infection models. This conclusion was obtained when deletion of ALS3 abrogated C. albicans virulence in the oral epithelial infection model, but not in a bloodstream infection model [69, 72]. Additionally, it has been reported that, in vitro, fungal-mediated acidification of the laboratory culture media is required to dissociate Fe 3+ from ferritin. Fe 3+ is transported into the fungal cytoplasm via the same reductive Fe uptake system described above for Ft [69]. Figure 3 shows the iron acquisitions systems in C. albicans.

C. albicans also possesses a third system of iron uptake based in the use of siderophores however, it is unclear whether C. albicans synthesizes its own siderophores. Siderophore activity has been reported for this species but its genome does not encode the known fungal biosynthetic enzymes [69, 73]. Nevertheless, C. albicans has been demonstrated to utilize exogenous ferrichrome-type siderophores via the Sit1 siderophore importer. Similar to ALS3, deletion of SIT1 abolishes C. albicans virulence in a reconstituted human epithelial infection model but not in a bloodstream infection model [69, 74]. Finally, it has been recently reported that Hap43, Sfu1, and Tup1 act coordinately and regulate iron acquisition, iron utilization, and other iron-responsive metabolic activities in C. albicans [75].

Candida glabrata is both a human fungal commensal and an opportunistic pathogen. It is the second most common cause of infection, surpassed only by C. albicans. This yeastis an intracellular pathogen that can survive phagocytosis and replicates within the host cell. C. glabrata infection is extremely difficult to treat due to its intrinsic antifungal resistance to azoles. The infections caused by this fungus are associated with a high mortality rate. Siderophore production is common among most microorganisms and is a major mechanism of Fe solubilization and acquisition. The very high Fe-binding contact observed for siderophores of fungal origin is approximately 10 30 M at pH 7. Several bacteria and fungi do not produce siderophores but have evolved transporters that allow them to utilize siderophores they themselves do not produce. These are called xenosiderophores [76].

Computational analysis of Sit1 identified sequence signatures that are characteristic of members of the Major Facilitator Superfamily of Transporters. In a study by Nevitt and Thiele (2011), Sit1 is described as the sole siderophore Fe transporter in C. glabrata, and the study demonstrates that this siderophore is critical for enhancing their survival in the face of the microbicidal activities of macrophages [77]. Within the Sit1 transporter, a conserved extracellular siderophore transporter domain (SITD) was identified that is important for the siderophore-mediated ability of C. glabrata to resist macrophage killing and is dependent on macrophage Fe status [77]. They suggested that the host’s iron status is a modifier of infectious disease that modulates the dependence on a distinct mechanism of microbial Fe acquisition. Iron-regulated CaSit 1 shares high homology with S. cerevisiae siderophore transporters and its deletion compromises utilization of fungal ferrichrome-type hydroxamate siderophores. The absence of an identifiable heme receptor in C. glabrata suggests that this pathogen may rely predominantly on the solubilization of the circulating exchangeable Fe pool to meet its requirements for Fe [76].

A study realized by Srivastava et al. (2014) described the molecular analysis of a set of 13 C. glabrata strains that were deleted for proteins and potentially implicated in Fe metabolism. The results revealed that the high-affinity reductive Fe uptake system is required for the utilization of alternate carbon sources and for growth under both in vitro Fe-limiting and in vivo conditions. Further, they showed for the first time that the cysteine-rich CFEM domain-containing cell wall structural protein CgCcw14 and the putative hemolysin CgMam3 are essential for maintenance of intracellular Fe content, adherence to epithelial cells, and virulence [78]. Additionally, they present evidence that the mitochondrial frataxin CgYfh1 is pivotal to Fe metabolism and conclude that high-affinity iron uptake mechanisms are critical virulence determinants in C. glabrata [78].

4.11. Cryptococcus neoformans

Cryptococcus neoformans is a fungal pathogen and a leading cause of pulmonary and central nervous systemic mycosis in immunocompromised individuals such as HIV-infected patients. For this reason, C. neoformans is sometimes referred to as an opportunistic fungus. It is a facultative intracellular pathogen. In human infection, C. neoformans is spread by inhalation of aerosolized spores (basidiospores) and can disseminate to the central nervous system where it can cause meningoencephalitis [79]. In the lungs, C. neoformans are phagocytosed by alveolar macrophages. Macrophages produce oxidative and nitrosative agents, creating a hostile environment, to kill invading pathogens. However, some C. neoformans can survive intracellularly in macrophages. Intracellular survival appears to be the basis for latency, disseminated disease, and resistance to eradication by antifungal agents [80]. One mechanism by which C. neoformans survives the hostile intracellular environment of the macrophage involves upregulation of expression of genes involved in responses to oxidative stress. C. neoformans has been considered an excellent model fungal pathogen to study iron transport and homeostasis because of its intriguing connection with virulence. Growing evidence suggests that the fungus is able to utilize several different iron sources available in the host, and that the intracellular or extracellular localization of the pathogen influences its iron acquisition strategy [80]. C. neoformans infects alveolar macrophages at this site, specifically in the acidic phagolysosome, free Fe 2+ is released from the host Ft and Tf. The reductive high-affinity Fe uptake system mediated by Cft1 and Cfo1 was characterized, its function was closely associated with the reduction of Fe 3+ at the cell surface by the reductase activity, and it was limited in the environment at neutral pH [79].

Therefore, C. neoformans could predominantly use an iron uptake system that is specifically responsive to the acidic intracellular niche, although Fe deprivation at an acidic pH no longer reduced the growth of the cft1 and cfo1 mutants. Moreover, a mutant lacking either CFT1 or CFO1 displayed attenuation of virulence and eventually caused disease in infected mice. These observations suggest that an as-yet unknown Fe uptake system, which is independent of the reductive high-affinity iron uptake system, may play a role in the acidic host microenvironment in a phagolysosome [79]. On the other hand, C. neoformans is able to utilize Tf through the reductive high-affinity iron uptake system and extracellular heme by Cig1 and the ESCRT complex however, more studies should be carried out to understand how C. neoformans directly liberates Fe from Tf as well as Hb and other heme-containing proteins [80]. It has been suggested that the gene CIR1 (Cryptococcus iron regulator) shares structural and functional features with other fungal GATA-type transcription factors for iron regulation [81]. Figure 4 shows the iron acquisitions systems in C. neoformans.

4.12. Leishmania spp.

Leishmaniasis is endemic in the tropics and neotropics. Clinical manifestations include skin lesions ranging from small cutaneous nodules to gross mucosal tissue destruction. The infection is transmitted to human beings and animals by sandflies. Leishmania parasites have a digenetic life cycle, alternating between the promastigote stage in the insect gut and the amastigote stage in macrophages of mammalian hosts. It has been postulated that Leishmania cells are equipped with diverse Fe acquisition mechanisms and are capable of utilizing various Fe sources, suggesting that Fe acquisition is essential for pathogenicity and that Fe deprivation could be an effective strategy for controlling leishmanial infections [82].

Like many other intracellular pathogens, Leishmania must be capable of acquiring Fe from the host milieu in order to thrive. In addition to Tf, the growth and survival of L. infantum and L. amazonensis amastigotes can be supported by Fe derived from hemoglobin and hemin [83]. The uptake of heme by intramacrophagic L. amazonensis amastigotes is mediated by the Leishmania heme response 1 (LHR1) protein. Furthermore, intracellular L. amazonensis also possesses a ferric reductase, the Leismania ferric iron reductase 1 (LFR1), which provides soluble Fe 2+ for transport across the parasite plasma membrane by the ferrous iron transporter, Leishmania iron transporter 1 (LIT1) [83, 84]. Moreover, LIT1-mediated Fe acquisition seems to be essential for the differentiation of L. amazonensis parasites from the sandfly promastigote form to the macrophage-adapted amastigote form [85].

Apart from the mechanisms of direct iron internalization, Leishmania parasites can also subvert the host’s Fe uptake systems to their own advantage. In fact, L. amazonensis amastigotes can obtain Tf by forcing the fusion of Tf-containing endosomes with the parasitophorous vacuole [86]. Alternatively, L. donovani is capable of decreasing the macrophage’s labile Fe pool, a process that triggers an increased surface expression of transferrin receptor 1 and internalization of Tf, thus permitting continuous provision of Fe to the parasite. This decrease in the labile Fe pool of activated macrophages has recently been proposed to be the result of the downregulation of the expression of SLC11A1 by a L. donovani-secreted peroxidase. Also, in line with these data, it has been reported that the expression of ferroportin is downregulated in the spleen of L. donovani-infected mice, which may contribute to an increased accumulation of iron inside macrophages. In Leishmania, a transferrin receptor-based mechanism for Fe uptake was also initially postulated, but this mechanism was not confirmed by subsequent studies [87]. Tf can reach the lysosome-like parasitophorous vacuoles where Leishmania resides in macrophages, but it appears to function mainly as a source of Fe 3+ for the sequential action of two surface-associated parasite molecules: the Fe 3+ reductase LFR1 and the LIT1 transporter, which directly promote Fe 2+ uptake. Intriguingly, the T. cruzi genome does not contain an obvious LIT1 orthologue, raising the possibility that this Fe 2+ -transporter represents a specific Leishmania adaptation to the low Fe environment of phagolysosomes [88]. Mutations in the lysosomal Fe efflux pump NRAMP1 confer susceptibility to Leishmania and other intravacuolar pathogens, reinforcing the conclusion that Leishmania needs a high-affinity transporter such as LIT1 to compete effectively for Fe within its parasitophorous vacuole [89]. On the other hand, L. amazonensis directly interferes with the Fe export function of macrophages, by inhibiting cell surface expression of Fpn1, but the mechanism by which this is achieved is still unknown [90].

4.13. Trypanosoma spp.

The amastigotes of the intracellular parasite Trypanosoma cruzi take up Fe-loaded Tf when grown in vitro, but the physiological significance of this process is unclear [91]. Tf is restricted to the lumen of the endocytic pathway and is therefore absent from the host cell cytosol, where intracellular amastigotes replicate. The bloodstream form of Trypanosoma brucei acquires Fe from Tf by receptor-mediated endocytosis by a process that is regulated by Fe availability. TrR is a heterodimeric complex encoded by two expression site-associated genes, ESAG6 and ESAG7, and shares no homology with the homodimeric mammalian Tf receptor. The binding of one molecule of Tf requires the association of both ESAG6 and ESAG7. In mammalian cells, the TfR mRNA is stabilized in iron-depleted cells due to the binding of IRPs to specific IREs. In T. brucei, this IRP-1 relation is not essential for Fe regulation of ESAG6 mRNA. In mammalian cells, the closely related IPR-2 can independently mediate the iron status via IREs. However, in trypanosomes, the presence of additional IRP-related proteins seems very unlikely. The T. brucei genome contains only one IRP-related gene, which suggests that a different mechanism, a different type of transacting factor, is responsible for Fe sensing and regulation of transferrin receptor mRNA in this protozoan [91, 92]. However, it is unknown how procyclic forms that cannot bind Tf acquire Fe. Additionally, the bloodstream-form of T. brucei acquires Fe by receptor-mediated endocytosis of host transferrin [93]. The mechanism(s) by which Fe is then transferred from the lysosome to the cytosol remains unresolved [94].

5. Conclusions

The use of Fe as a cofactor in basic metabolic pathways is essential to both pathogenic microorganisms and their hosts. It is also a pivotal component of the innate immune response through its role in the generation of toxic oxygen and nitrogen intermediates. During evolution, the shared requirement of micro- and macroorganisms for this important nutrient has shaped the pathogen-host relationship [14]. Two general mechanisms of Fe acquisition in intracellular parasites have been described: siderophore-mediated Fe acquisition by cognate receptors and receptor-mediated Fe acquisition from host Fe-binding proteins [14]. Intracellular microorganisms have evolved a variety of siderochromes, which are special ligands that can dissolve insoluble Fe 3+ and facilitate its transport into the cell in order to acquire Fe from Tf and other Fe-proteins in the host. The success of intracellular parasites seems to be related mainly to their ability to take up Fe from the protein Tf [12]. Once ingested by macrophages, intracellular parasites are taken up by phagosomes via endocytosis. Acidification of the phagosome permits the iron to be released from Tf, and, in this way, some pathogens can gain access to this element [12].

Bacteria use the protein ferritin or bacterioferritin to store Fe. These are ubiquitous Fe storage proteins that play a fundamental role in cellular Fe homeostasis and have similarities with Ft that is found in mammals. Bacterial Fts have the capacity to store very large amounts of Fe as a Fe 3+ mineral inside its central cavity. In times of Fe deprivation, some bacteria require that iron be released from Ft mineral stores in order to maintain their metabolic rate and growth. In times of Fe repletion, intracellular microorganisms must regulate the genes required for Fe acquisition, but this mechanism has not been fully characterized [45, 61]. Transferrin and its receptor (TfR1) play an important role during infection of macrophages with bacterial pathogens that prefer an intracellular lifestyle. Expression of TfR1 can in turn be modulated by bacterial infections. Some pathogens actively recruit TfR1 to the bacterium-containing vacuole [29, 45].

The notion is conceivable that intracellular pathogens reside in phagosomal compartments to modulate Fe regulatory proteins, thereby increasing their Fe availability, but this notion is still speculative. The Fe acquisition process often begins when cell surface receptors recognize Fe 3+ complexes and ultimately ends when cytoplasmic membrane (CM) transporters internalize and, in some cases, reduce the metal to Fe 2+ , which then enters cytoplasmic metabolic pools [14]. Despite many advances, the exact role of Fe acquisition systems in vivo and their effects in pathogenic virulence remain to be determined.

Conflict of Interests

The authors declare that they have no conflict of interests.


This work was supported by a grant from CONACYT (CB-2014-236546) and PROFAPI-UAS (2014). The authors apologize to their colleagues whose work they were not able to cover or cite in this brief review.


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Copyright © 2015 Nidia Leon-Sicairos et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

What You Need To Know About Infectious Disease

The 1918 influenza pandemic (the so-called &ldquoSpanish&rdquo flu) is estimated to have killed how many people worldwide?

The 1918 influenza pandemic is estimated to have killed between 50 million and 100 million people worldwide. Many of those deaths were due to the effects of pneumococcal pneumonia, a secondary complication of flu for which no antibiotics existed in 1918.

The 1918 influenza pandemic is estimated to have killed between 50 million and 100 million people worldwide. Many of those deaths were due to the effects of pneumococcal pneumonia, a secondary complication of flu for which no antibiotics existed in 1918.

The 1918 influenza pandemic is estimated to have killed between 50 million and 100 million people worldwide. Many of those deaths were due to the effects of pneumococcal pneumonia, a secondary complication of flu for which no antibiotics existed in 1918.

Infectious Disease Defined

The physical and functional unit of heredity made up of DNA. Every individual has two copies of each gene, one inherited from the mother and the other from the father.

National Academies Press

Search the National Academies Press website by selecting one of these related terms.

Goodman's Medical Cell Biology

Goodman’s Medical Cell Biology, Fourth Edition, has been student tested and approved for decades. This updated edition of this essential textbook provides a concise focus on eukaryotic cell biology (with a discussion of the microbiome) as it relates to human and animal disease. This is accomplished by explaining general cell biology principles in the context of organ systems and disease.
This new edition is richly illustrated in full color with both descriptive schematic diagrams and laboratory findings obtained in clinical studies. This is a classic reference for moving forward into advanced study.

Goodman’s Medical Cell Biology, Fourth Edition, has been student tested and approved for decades. This updated edition of this essential textbook provides a concise focus on eukaryotic cell biology (with a discussion of the microbiome) as it relates to human and animal disease. This is accomplished by explaining general cell biology principles in the context of organ systems and disease.
This new edition is richly illustrated in full color with both descriptive schematic diagrams and laboratory findings obtained in clinical studies. This is a classic reference for moving forward into advanced study.

15.2 Eukaryote Regulation

In Eukaryotes, a variety of mechanisms regulate gene expression

1. chromatin structure
2. transcriptional control (operons)
3. post transcriptional control
4. translationslation control
5. post translational control

Chromatin Structure

DNA is wound around a core of eight protein molecules, the result resembles beads on a string. The protein molecules are histones and each individual bead is called a nucleosome

Females have two X chromosomes, but it is believed that one of the inactivates. The expression of the genes located on the X chromosome depends on which X is active (random).

Calico cats have the patchwork color because the genes for black and orange colors are located on the X chromosome

Part 2: Exploring the “New Microbiology” with the bacterial pathogen Listeria monocytogenes

00:00:07.22 So, I am Pascale Cossart from the Pasteur Institute,
00:00:10.18 where I am a professor
00:00:12.13 and I am also a Senior International Research Scholar
00:00:16.01 from the Howard Hughes Medical Institute.
00:00:19.16 This is the second part of my three talks,
00:00:23.15 and I would like to discuss how
00:00:27.08 Listeria monocytogenes
00:00:30.00 has contributed to the new field of.
00:00:32.24 the new microbiology.
00:00:35.09 So, what do I mean by new microbiology?
00:00:37.16 By new microbiology, I mean that there is
00:00:41.10 a renaissance in fundamental microbiology
00:00:44.13 because of the use of new approaches,
00:00:47.12 and these new approaches
00:00:50.03 are generating really new concepts.
00:00:52.08 So, the new approaches, the new tools, the new methods,
00:00:57.00 are really including genetics, transcriptomics, proteogenomics,
00:01:01.01 imaging, live-cell imaging, and single-cell analysis, and of course animal models.
00:01:08.19 The new concepts which are generated
00:01:11.17 by these new approaches are, for example,
00:01:16.01 new concepts in bacterial regulation
00:01:19.02 and, most importantly,
00:01:21.12 RNA-mediated regulation
00:01:24.18 is really changing our view of
00:01:27.18 how bacterial genes are expressed.
00:01:30.13 Another new concept is the fact that bacteria
00:01:35.06 are living in microbial assemblies,
00:01:37.18 either pure microbial assemblies or mixed microbial assemblies,
00:01:41.02 not only with bacteria,
00:01:44.05 but also with other microorganisms.
00:01:47.19 The field of the study of bacterial communication is really exploding.
00:01:51.03 Bacteria communicate via chemicals
00:01:53.14 or via other signals, sometimes with peptides,
00:01:56.20 and this is also something which is really interesting and important.
00:02:01.06 Bacterial cell biology is also exploding
00:02:04.20 and imaging, which has been critical in cell biology of eukaryotic cells,
00:02:10.13 is now also allowing us to have
00:02:14.19 access to really details in gene expression,
00:02:17.17 in how proteins are sorted in the bacterial cells,
00:02:20.19 and bacteria are no longer considered as little bags,
00:02:29.19 which are expressing proteins and other components.
00:02:32.08 The new concept which is really also increasing
00:02:35.19 is the concept of persistence
00:02:37.20 and this is particularly important in the field of bacterial pathogenesis.
00:02:42.21 persistence and dormancy.
00:02:45.15 Finally, the role of microbiota in health and disease
00:02:49.20 is invading not only microbiology
00:02:51.20 but also immunology, neurobiology, developmental biology.
00:02:56.16 So, today, I would like just to talk about
00:03:01.04 how Listeria has contributed to this new field of new microbiology.
00:03:05.17 I'll remind you what I said in the first part of my talk.
00:03:09.00 Listeria monocytogenes is a bacteria
00:03:12.06 which is present in the environment.
00:03:14.21 It's motile at low temperature
00:03:17.18 due to this flagella,
00:03:20.01 but it's not motile at high temperature.
00:03:22.20 So, this is a bacterium which is ubiquitous
00:03:25.11 and can easily contaminate food products.
00:03:28.16 Contaminated food products lead to disease
00:03:32.05 and it's particular important in
00:03:35.16 immunocompromised individuals, old people, newborn babies,
00:03:39.17 and also pregnant women.
00:03:43.06 So, the successive steps of Listeria infections are as follows:
00:03:48.20 bacteria arrive in the intestine
00:03:52.12 via contaminated food products
00:03:55.22 bacteria are able to cross the intestinal barrier
00:03:58.03 -- this is a unique property
00:04:00.04 then the bacteria, via the blood,
00:04:02.24 are able to reach the liver and the spleen
00:04:06.09 and then they disseminate to deeper organs
00:04:09.19 such as the brain and the placenta.
00:04:14.00 At the cellular level, the bacteria are invasive,
00:04:18.15 which means that they are able to enter into cells
00:04:22.09 which are nonphagocytic.
00:04:24.02 So, they enter into cells via two proteins
00:04:28.23 which are called internalin and InlB.
00:04:32.08 Internalin is also called InlA.
00:04:35.00 Then, the bacteria are trapped in the vacuole.
00:04:38.00 They are able to escape from the vacuole
00:04:40.19 thanks to the action of lysteriolysin O,
00:04:44.18 a toxin which is called, also, LLO.
00:04:49.22 Sometimes, LLO is helped by two phospholipases,
00:04:52.14 which are called PlcA and PlcB.
00:04:56.02 Then, the bacteria, free in the cytosol,
00:04:59.08 not only divide, but they are able to move.
00:05:02.10 And then move because they are able to recruit actin,
00:05:05.17 polymerize this actin,
00:05:07.17 and propel themselves in the cytosol.
00:05:10.00 Not only do they move,
00:05:14.01 but they are able to spread from one cell to the other
00:05:16.13 and they generate, in that case,
00:05:18.19 a two-membrane vacuole, which is lysed, again,
00:05:23.14 by LLO and by the two phospholipases.
00:05:27.21 So, the bacteria disseminate from one cell to the other.
00:05:29.24 And they do that by the factors that I have mentioned,
00:05:33.00 and these factors are, interestingly,
00:05:36.13 located on two main loci of the chromosome of the bacteria,
00:05:43.01 and these genes are co-regulated by the protein PrfA.
00:05:47.00 So, PrfA is a protein which is similar
00:05:50.13 to the CAP protein of Escherichia coli.
00:05:55.03 So, the CAP protein is the cyclic-AMP receptor protein
00:06:01.11 and it's also called CRP.
00:06:03.03 So, PrfA is similar to CRP.
00:06:05.13 PrfA co-activates all the genes which are on this slide.
00:06:09.24 What is interesting is that, at low temperature,
00:06:13.13 when the bacteria is in the environment,
00:06:16.07 all these virulence factors are not expressed.
00:06:19.07 So, we wondered what was the case,
00:06:22.03 what was the situation for PrfA.
00:06:24.15 And we could show that, at low temperature, PrfA is also not present.
00:06:29.17 But the message for PrfA is present at low temperature.
00:06:35.21 And what we found is that the PrfA message,
00:06:38.16 at low temperature,
00:06:40.23 is having a very interesting structure
00:06:44.17 that you see on this slide.
00:06:47.03 So, at low temperature, the message
00:06:49.21 is forming this stem-and-loop structure,
00:06:52.01 which prevents the ribosome
00:06:56.16 from getting access to the ribosome binding site,
00:06:59.08 the Shine-Delgarno sequence, SD on this slide.
00:07:03.00 At higher temperature, this structure,
00:07:05.17 this stem-and-loop structure,
00:07:08.08 opens up and then the ribosome has access to the Shine-Delgarno sequence,
00:07:13.01 and the Shine-Delgarno sequence allows
00:07:17.14 the translation of the message, PrfA is made,
00:07:19.21 and all the virulence factors are made in the same time.
00:07:22.18 So, this is a beautiful example of
00:07:27.23 a new type of regulation of virulence factors at high temperature.
00:07:31.17 In the last two years, there have been papers published
00:07:37.08 which show that, in the case of Yersinia,
00:07:40.18 this is also the case.
00:07:43.13 the virulence factors are expressed at higher temperatures.
00:07:45.19 This had been predicted a long time ago, but was really recently shown.
00:07:48.18 In the case of Neisseria,
00:07:51.08 there is also temperature regulation of virulence factors.
00:07:54.03 So, this is a really interesting property of Listeria
00:07:58.04 virulence factors are regulated by a thermosensor.
00:08:00.20 I would like now to come back to the post-genome studies.
00:08:06.03 So, we performed the sequencing of the genes of Listeria
00:08:10.06 to be able to have access
00:08:14.08 to biodiversity, virulence, and global gene expression.
00:08:16.03 So, we very rapidly used high density membrane.
00:08:20.00 We could show that PrfA is not only expressing
00:08:23.12 or regulating the genes that I showed you before,
00:08:26.05 but also all these genes that are on this slide,
00:08:29.08 including the bile salt hydrolase
00:08:31.18 that I discussed in Part 1.
00:08:33.17 But we thought that we wanted to get
00:08:36.16 access to the real transcriptome of Listeria,
00:08:38.23 and we decided to use tiling arrays,
00:08:41.22 not only to have access to the transcriptome of the genes
00:08:46.14 that we had annotated during the annotation of the genome,
00:08:49.16 but also to have access to the small RNAs,
00:08:52.16 because the field was exploding at the time.
00:08:56.24 So, we generated Listeria-specific tiling arrays
00:08:59.04 and we decided to look at the transcriptome of Listeria
00:09:03.02 in many, many conditions.
00:09:05.03 that is, different temperatures,
00:09:07.18 in vitro but also in vivo
00:09:09.15 -- that means, in the intestine of infected mice --
00:09:12.03 and also using different mutants.
00:09:14.11 So, I don't have time to tell you the results,
00:09:16.24 but I would like to tell you, on this slide,
00:09:20.01 that this study has led to the
00:09:23.03 identification of 50 non-coding RNAs
00:09:26.06 -- the number has now really increased,
00:09:28.18 I will come back to that.
00:09:30.15 But what was interesting in the study was that
00:09:34.15 we could show that there are small RNAs
00:09:37.10 which were not constitutively expressed -
00:09:39.11 - they were differentially expressed according to the conditions --
00:09:43.11 and we had also some non-coding RNAs, called small RNAs,
00:09:49.01 which were present in monocytogenes and were absent in Listeria innocua.
00:09:52.04 For example, rli38, which is present in monocytogenes,
00:09:56.18 absent in innocua,
00:09:58.16 highly expressed in the blood of infected animals,
00:10:01.09 when deleted, is really affecting virulence.
00:10:04.24 So, this was one of the first small RNAs which was affecting virulence.
00:10:09.11 So, we discovered a lot of things during this study,
00:10:13.12 and in particular we were interested in antisense mechanisms.
00:10:18.21 For example, we. and this was totally surprising.
00:10:21.22 we discovered three long antisense RNAs.
00:10:24.16 These long antisense RNAs
00:10:27.05 are opposite to annotated open reading frame.
00:10:30.17 We had also overlapping 3'-UTRs.
00:10:34.02 We also had overlapping 5'-UTRs.
00:10:38.01 And I must say that,
00:10:40.18 when we published these results, we were very stringent
00:10:44.02 and we knew that there would be other cases with a structure
00:10:47.13 that was not accessible when we annotated the genome
00:10:54.10 a long time ago.
00:10:56.05 So, we decided that we had to do one other technique,
00:10:58.15 which was RNAseq.
00:11:01.08 So, we performed the whole-genome transcriptomics,
00:11:04.14 so that means we had access to.
00:11:07.05 and we also used the sophisticated technique
00:11:10.04 which allows to distinguish
00:11:12.23 between transcriptional start sites and processing sites.
00:11:15.14 So, we could identity the transcriptional start sites
00:11:18.06 on one direction and the other direction,
00:11:21.04 that means on one strand and the other strand of the DNA.
00:11:23.12 We could also distinguish antisense.
00:11:26.14 the promoter for antisense RNA
00:11:30.16 and also transcriptional start sites for small RNA,
00:11:34.06 which are in between two protein-coding genes.
00:11:38.21 So, this was a lot of data,
00:11:43.11 and we wanted to give that to the scientific community,
00:11:46.24 so we decided to build a browser.
00:11:49.18 And the browser that we have generated is, in fact,
00:11:54.18 the browser where we have included not only the RNAseq data,
00:11:57.06 but we decided to include also the tiny RNA data and the tiny RNA data
00:12:01.05 which were collected by other groups.
00:12:03.10 So, all together, all these data are available on the website
00:12:09.11 which is indicated here.
00:12:11.04 So, that means, if you go to this website,
00:12:13.10 you can see how Listeria is transcribed
00:12:16.03 in several conditions,
00:12:19.00 and I'm just going to show you that
00:12:22.02 you can go all along the genome and see how the genes are expressed,
00:12:25.09 and see one promoter, here,
00:12:28.02 a promoter going in the other direction, and we can.
00:12:31.24 you can compare your gene with the genome of Listeria in different conditions.
00:12:37.18 You see that this is a lot of data
00:12:41.12 which is in this browser,
00:12:43.16 and I would like to focus now on the antisense RNA.
00:12:47.10 So, I said already that we had been surprised in the tiny RNA data analysis
00:12:53.17 that we had identified long antisense RNA.
00:12:59.06 So, in this RNAseq study,
00:13:01.14 we identified short antisense and long antisense RNA.
00:13:04.03 Concerning the long antisense RNA,
00:13:06.15 there was one class which was really interesting,
00:13:09.01 and this class is a class
00:13:12.02 where you have a long antisense RNA
00:13:14.10 which is antisense for a gene,
00:13:17.08 but which acts as a messenger for genes
00:13:21.07 which are transcribed in the other direction.
00:13:23.19 So, in the example which is given on this slide,
00:13:26.16 you see that this long antisense RNA
00:13:29.18 is regulated by sigmaB.
00:13:31.23 So, by using a sigmaB mutant, we could
00:13:36.05 show the effect of this long antisense RNA.
00:13:38.20 And in this sigmaB mutant, for example,
00:13:41.10 we could show that the efflux pump was highly expressed
00:13:43.22 and that the permease genes,
00:13:46.13 which are in the other direction,
00:13:48.24 were less expressed.
00:13:50.22 So, we came up with a new concept
00:13:53.11 that we have named the excludon.
00:13:55.10 So, the excludon is a genetic locus
00:13:58.13 where a long antisense RNA
00:14:01.03 can act as an antisense and as a messenger RNA,
00:14:05.08 regulating genes which opposite
00:14:08.18 or mutually exclusive functions.
00:14:10.10 You realize that you can downregulate one gene
00:14:13.12 and upregulate genes
00:14:16.15 which are in the opposite direction
00:14:19.10 just with one long antisense RNA.
00:14:21.13 And we have found that there are several examples
00:14:25.01 in the Listeria genome
00:14:27.02 and in other genomes.
00:14:29.11 I think it's a new concept that.
00:14:32.10 you can only have access if you do RNAseq.
00:14:34.16 It's not by notating your genome that you will have access to this type of data.
00:14:39.08 So, this is for the antisense RNA.
00:14:41.18 Now, I'm going to a new concept,
00:14:44.14 which is riboswitches.
00:14:48.11 So, riboswitches, which have been discovered by other groups
00:14:53.20 several years ago,
00:14:57.03 can be classified in two classes:
00:14:59.04 the translational riboswitches
00:15:01.17 and the transcriptional riboswitches.
00:15:04.23 So, riboswitches are a structure which are located in the 5'-UTR,
00:15:09.03 or the 5'-untranslated region,
00:15:12.20 of messenger RNA,
00:15:15.04 and these 5' regions can form
00:15:19.11 different types of structure depending on the binding of a ligand.
00:15:23.22 So, you see that, if there is binding of a ligand,
00:15:28.02 for example, S-adenosylmethionine, SAM,
00:15:30.11 you see that you have a structure which is changing,
00:15:34.22 and in the case of the translational riboswitches
00:15:37.18 the ribosome binding site will be hidden
00:15:41.19 and will prevent the expression of the downstream gene.
00:15:47.05 In the case of the transcriptional riboswitches,
00:15:50.18 if there is binding of the ligand, again, S-adenosylmethionine,
00:15:55.24 to the 5'-UTR of the message,
00:15:58.02 there is the formation of what is called the terminator,
00:16:00.24 and then there is the generation of a sole transcript,
00:16:04.23 that you see here,
00:16:07.03 which prevents the expression of the downstream genes.
00:16:09.20 So, riboswitches are generally
00:16:16.19 regulating metabolic genes,
00:16:18.13 which are involved in, for example, the biosynthesis of amino acids,
00:16:22.03 but they are also involved in many other cases.
00:16:24.14 So, riboswitches can bind amino acids,
00:16:28.16 they can bind tRNAs, they can bind metals,
00:16:32.18 they can bind different types of structures.
00:16:37.02 I will come back to that in five minutes.
00:16:40.20 So, in the case of Gram-positive bacteria, like Listeria,
00:16:43.23 it's essentially transcriptional riboswitches which are in action.
00:16:48.22 We found several unusual riboswitches
00:16:52.22 when we were doing our tiny RNA analysis.
00:16:57.12 So, if you remember, we were doing the tiny RNA analysis --
00:17:02.00 that means we extracted RNA in different conditions
00:17:04.15 -- then we were putting the RNA on the tiling arrays
00:17:07.19 and we were analyzing where we had transcription.
00:17:11.07 And it was really amazing that we found several cases
00:17:14.17 where we had riboswitches,
00:17:17.04 downstream genes, and upstream of.
00:17:21.00 and not upstream of open reading frames.
00:17:24.11 So, it was something that was
00:17:27.16 a bit intriguing for us.
00:17:29.20 But, in the case of the B12, vitamin B-12
00:17:33.15 riboswitch that I am showing you in this slide,
00:17:36.02 we had another piece of data which led to
00:17:40.12 a very interesting story.
00:17:42.11 So, as you can see here, the riboswitch,
00:17:45.00 which is in green, is highly expressed in these conditions,
00:17:48.16 and the gene which is downstream is pocR,
00:17:54.06 which is located in the other direction,
00:17:56.08 but there is another small RNA,
00:17:59.10 which is called RliH,
00:18:01.15 which has absolutely no transcriptional start site.
00:18:04.04 So, this was a really intriguing region.
00:18:07.08 Not only was it intriguing, but it was interesting.
00:18:09.12 Why?
00:18:11.23 Because pocR, the gene of Listeria
00:18:14.17 which is similar to the pocR gene of salmonella,
00:18:16.20 is predicted to be a pleiotropic regulator.
00:18:21.04 Indeed, in salmonella,
00:18:26.11 pocR is involved in the co-regulation of genes
00:18:30.10 which are involved in the utilization of propanediol
00:18:33.20 in the intestine.
00:18:35.18 And it's been very well demonstrated
00:18:38.17 in the case of salmonella
00:18:40.18 that these genes are conferring
00:18:44.03 a serious advantage to salmonella
00:18:47.03 compared to other bacteria, when they are in the intestine.
00:18:51.23 So, we were wondering, what was the situation in Listeria?
00:18:54.14 And it was a postdoc in the lab, J.R. Mellin,
00:18:59.18 who made this hypothesis that maybe this Rli39
00:19:04.04 was the riboswitch for a long antisense RNA
00:19:06.22 which would be antisense to pocR.
00:19:11.02 And to make a long story short,
00:19:13.15 this is really what we found.
00:19:15.16 This riboswitch is regulating an antisense RNA.
00:19:19.22 So, the model that we had in mind
00:19:22.14 and that we have been able to prove is as follows:
00:19:25.12 in the presence of propanediol
00:19:28.11 and in the absence of B12,
00:19:30.15 the long antisense is made
00:19:33.16 but as soon as B12 is present,
00:19:36.07 B12 binds to the riboswitch,
00:19:38.21 the riboswitch leads to the expression
00:19:42.10 of a short transcript,
00:19:44.09 and the short transcript is not able to act as
00:19:48.20 an antisense for pocR.
00:19:50.18 So, we have a lot of pocR, we have a lot of the pdu gene expression,
00:19:54.11 and we end up with a bacteria
00:19:58.18 which is able to use propanediol,
00:20:01.08 if propanediol is present.
00:20:03.20 So, if I summarize the situation,
00:20:06.11 the unusual B12 riboswitch in that region is.
00:20:11.00 is regulating the expression of an antisense for pocR,
00:20:16.19 which is the pleiotropic regulator of the propanediol transition genes.
00:20:21.10 What I did not say is that all these genes are encoding for proteins
00:20:26.23 which require B12 for their activity.
00:20:31.01 So, you see that you have B12,
00:20:33.01 which is regulating the expression of the antisense,
00:20:37.18 and there is only expression of the propanediol utilization genes
00:20:43.05 if B12 is present.
00:20:45.23 So, I think it's a wonderful example
00:20:49.20 of the ending of a long story
00:20:52.13 where we have done the annotation of the genome,
00:20:55.14 we did the transcriptome by tiny RNA, we did the RNAseq,
00:20:59.03 and now we are showing that the riboswitch
00:21:02.15 is really regulating an antisense RNA
00:21:05.05 and this is, in fact, the second example of a riboswitch
00:21:08.17 which is regulating an antisense RNA.
00:21:11.13 So, propanediol, where does it come from?
00:21:14.14 Propanediol is the product of the catabolism.
00:21:18.16 is the product of. is.
00:21:21.24 propanediol is made by commensals in the intestines
00:21:24.16 and it's the byproduct of a different sugars,
00:21:28.10 like fructose and mannose.
00:21:30.20 So, really, propanediol is made by commensals in the intestine
00:21:36.09 and, surprisingly,
00:21:39.16 it was the time where we were interested in the intestinal phase of the infection and the role of microbiota
00:21:47.01 in the intestinal phase of the infection.
00:21:49.02 And what we had in mind was to decipher
00:21:51.13 what was the role of the commensals
00:21:53.19 on the expression of genes in the mouse intestine
00:21:56.17 and on the expression of genes in the Listeria monocytogenes.
00:22:00.20 So, we. what we had done was
00:22:04.14 a very, very reductionist approach,
00:22:07.13 which is that we decided that
00:22:10.13 we would take germ-free mice, axenic mice,
00:22:13.04 we would infect them with Listeria monocytogenes
00:22:17.14 in one case,
00:22:20.05 or we would take the germ-free mice,
00:22:22.13 put Lactobacilli,
00:22:24.21 and then infect with Listeria monocytogenes.
00:22:27.09 And we wanted to study both the mouse transcriptome
00:22:30.24 and the Listeria monocytogenes transcriptome.
00:22:34.09 So, we found that the Lactobacilli
00:22:37.06 are really affecting the mouse response
00:22:40.00 and we found that, in fact,
00:22:43.00 the Lactobacilli are protecting mice
00:22:47.23 against Listeria infection.
00:22:50.04 As you can see, there is an effect of the lactobacilli
00:22:53.15 on the efficiency of the infection.
00:22:56.23 But what I would like, really, to highlight here is that, in fact,
00:23:00.24 there is an impact of the Lactobacilli on the Listeria gene expression.
00:23:05.03 And among the genes which are highly affected
00:23:08.15 by the presence of bacteria in the intestine,
00:23:11.16 we found that the propanediol diol catabolism genes,
00:23:16.01 the pdu genes,
00:23:18.19 were among the most highly regulated
00:23:21.21 by the presence of the Lactobacilli.
00:23:25.05 So, this is really to show you that
00:23:28.04 these utilization genes are critical for the survival,
00:23:31.02 for the persistence,
00:23:33.15 for the infection by Listeria monocytogenes.
00:23:36.06 And what is really interesting is that,
00:23:38.22 among the highly regulated genes in the intestine,
00:23:42.09 which are really regulated by the fact that
00:23:45.03 if you pre-incubate with Lactobacilli,
00:23:48.09 you change, you reshape the transcriptome,
00:23:51.18 you also end up with the ethanolamine utilization genes,
00:23:55.15 which are also highly regulated.
00:23:57.19 And if I tell you that, it's because we are, at present,
00:24:01.21 we're working on these ethanolamine utilization genes,
00:24:04.19 and we are also demonstrating that
00:24:09.00 there is a riboswitch regulated by vitamin B12,
00:24:11.05 which is regulating the ethanolamine utilization genes.
00:24:15.19 In fact, there are many, many riboswitches
00:24:19.18 which, we predict,
00:24:22.24 will be able to regulate non-coding RNAs, antisense RNAs.
00:24:27.07 And we have performed bioinformatics studies
00:24:30.21 and we could show.
00:24:33.04 and this is not highly visible on this slide.
00:24:35.14 we could show that there are many "isolated" riboswitches,
00:24:38.11 which are not present upstream of open reading frames,
00:24:42.18 but upstream of other.
00:24:45.18 of reading frames which are oriented in a different orientation.
00:24:49.20 We have also found that there are many riboswitches
00:24:52.21 which are very far from the downstream open reading frame,
00:24:57.02 and we really predict that
00:25:01.13 there were will be other antisense non-coding RNA
00:25:04.05 which would be regulated by riboswitches in many, many bacteria.
00:25:07.13 So, with that, I would like to conclude that,
00:25:13.02 by studying how Listeria is behaving,
00:25:15.23 either in the mammalian cells
00:25:18.20 or in the total organism,
00:25:21.03 we have discovered a lot of new types of bacterial regulation.
00:25:27.21 I would like to remind you that I mentioned
00:25:30.17 the thermoregulation by an RNA thermosensor,
00:25:33.21 which is regulating PrfA,
00:25:36.13 the protein which is co-activating all the virulence genes.
00:25:40.12 I have told you about the notion of the excludon,
00:25:44.14 and the excludon is this genetic locus
00:25:47.00 where you have this long antisense RNA
00:25:49.22 which is acting as an antisense for a gene
00:25:54.14 and it's acting as a messenger RNA for genes
00:25:57.13 which are located in opposite orientation
00:25:59.18 to the gene which is regulated by the antisense.
00:26:02.06 by the antisense.
00:26:04.07 So, in that case, the antisense is really acting
00:26:06.20 as the messenger RNA.
00:26:08.24 So, I didn't have time to tell you about microbial assembly
00:26:13.02 or bacterial communication,
00:26:15.10 but I have shown you that one bacterium
00:26:18.05 -- the Lactobacilli --
00:26:20.20 are able to reshape the transcriptional program of Listeria monocytogenes
00:26:24.04 inside the mouse intestine,
00:26:26.16 and I showed you that the propanediol utilization genes
00:26:30.14 and the ethanolamine genes
00:26:34.09 are highly affected by the presence of the Lactobacilli in the intestine.
00:26:40.00 So, with that, I would like to say that, since 1986,
00:26:43.07 since we're been working on Listeria,
00:26:46.11 I think the field of microbiology has really changed,
00:26:49.07 and Listeria has contributed to that.

The biology of Trichomonas vaginalis in the light of urogenital tract infection

The human pathogen Trichomonas vaginalis is a parasitic protist. It is a representative of the eukaryotic supergroup Excavata that includes a few other protist parasites such as Leishmania, Trypanosoma and Giardia. T. vaginalis is the agent of trichomoniasis and in the US alone, one in 30 women tests positive for this parasite. The disease is easily treated with metronidazole in most cases, but resistant strains are on the rise. The biology of Trichomonas is remarkable: it includes for example the biggest protist genome currently sequenced, the expression of about 30,000 protein-encoding genes (and thousands of lncRNAs and pseudogenes), anaerobic hydrogenosomes, rapid morphogenesis during infection, the secretion of exosomes, the manipulation of the vaginal microbiota through phagocytosis and a rich strain-dependent diversity. Here we provide an overview of Trichomonas biology with a focus on its relevance for pathogenicity and summarise the most recent advances. With some respect this parasite offers the opportunity to serve as a model system to study certain aspects of cell and genome biology, but tackling the complex biology of T. vaginalis is also important to better understand the effects that accompany infection and direct symptoms.

Keywords: Adhesion Host–parasite interaction Morphogenesis Secreted molecules Surface proteins Trichomonas vaginalis.

Materials and methods

DNA and RNA isolation

The genotype used for whole genome de novo sequencing was ‘Zhongzhi No. 13’, an elite sesame cultivar that has been introduced to most of the major sesame planting areas over the past 10 years. Genomic DNA was extracted from leaves with a standard CTAB (Cetyl trimethylammonium bromide) extraction method [51]. The materials used for RNA-Seq to analyze lipid and sesamin synthesis were three sesame accessions with different lipid and sesamin content (Table S1 in Additional file 1). The seeds of 10, 20, 25 and 30 DPA plants were sampled for RNA-Seq. The procedure described by Wei et al. [17] was used for RNA extraction and sequencing (or see Additional file 1).

Whole genome shotgun sequencing and assembly

We carried out whole genome shotgun sequencing with the Illumina Hiseq 2000 platform. Eight paired-end sequencing libraries with insert sizes of approximately 180 bp, 500 bp, 800 bp, 2 kb, 5 kb, 10 kb and 20 kb were constructed, which generated a total data amount of 99.54 Gb. To reduce the effect of sequencing error on assembly, we applied a series of stringent filtering steps on read generation (see Supplementary Note in Additional file 1). After the above quality-control and filtering steps, 54.46 Gb of clean data, approximately 150-fold coverage of the predicted genome size, remained (Table S2 in Additional file 1 Data S1 in Additional file 2). The quality and quantity of the filtered data were checked by the distributions of the clean reads from every library (Figure S1 in Additional file 1). For all of the 37.63 Gb of clean data from short-insert size libraries, a custom program based on the k-mer frequency methodology was used to trim reads and correct bases [26]. Next, all of the remaining data were used for de novo genome assembly. We carried out the whole genome assembly using SOAPdenovo [30, 52].

Contig construction

First, we split the reads from the short-insert size libraries into k-mers (k = 71) and constructed a de Bruijn graph. We then simplified the graph referring to the parameters, and lastly connected the k-mer path to produce the contig file.

Scaffold construction

All usable reads were realigned onto the contig sequences the amount of shared paired end relationships between each pair of contigs and the rate of consistent and conflicting paired-ends were calculated to construct the scaffolds step by step, from short-insertion-size paired ends to long-insertion-size paired ends, and finally, scaffolds.

Gap filling

We used the tool GapCloser [53] to close the gaps inside the constructed scaffolds, which were mainly composed of repeats masked before scaffold construction. We used the paired-end information to retrieve the read pairs that had one end mapped to the unique contig and the other located in the gap region. Then, we preformed local assembly for these collected reads. Finally, about 274 Mb of the sesame genome was assembled, 98.8% of which is non-gapped sequences (Additional file 1).

Estimation of genome size by flow cytometry

Flow cytometry was used to determine the DNA content of sesame [54]. Sesame samples and reference material were analyzed on an EPICS Elite ESP cytometer (Beckman-Coulter, Hialeah, FL, USA) with an air-cooled argon laser (Uniphase) at 488 nm using 20 mW. Salmon erythrocytes (2.16 pg/1C) were used as internal biological reference materials. Nuclear DNA content (in picograms) of sesame samples was estimated according to the following equation: 1C nuclear DNA content = (1C reference in picograms × Peak mean of sesame)/(Peak mean of reference). The number of base pairs per haploid genome was calculated based on the equivalent of 1 pg DNA = 978 Mb [55]. As a result, the C-value of sesame was estimated to be 0.34 pg/1C, and its genome size was estimated to be approximately 337 Mb (Figure S3 in Additional file 1).

Anchoring of genome assembly to sesame genetic map

We used a combination method of specific length amplified fragment sequencing and experiment marker analysis to construct a new genetic map using 107 F2 lines derived from the Zhongzhi No.13/ZZM2289 population. In total, 2,719 SNPs, 97 insertions and deletions (indels) and 2,282 SSR markers were developed and screened against the population. After filtering the markers with low PCR quality, those having no polymorphism and those showing significantly distorted segregation in the population, the retained 45 indels, 259 SNPs and 124 SSR markers were used to construct the genetic map using JoinMap 3 software (Kyazma BV, Wageningen, Netherlands). Finally, we successfully constructed a genetic map that spans 1790.08 cM and has 406 markers, including 39 indels, 251 SNPs and 116 SSR markers. Based on the genetic map, 150 large scaffolds were anchored onto 16 pseudomolecules (see details in the Supplementary Note 3 in Additional file 1).

Gene structure prediction and function annotation

To predict genes in the assembled genome, we used both homology-based and de novo methods. For the homology-based prediction, A. thaliana, grapevine, castor, and potato proteins were mapped onto the assembled genome using Genewise [56] to define gene models. For de novo prediction, Augustus [57] and GlimmerHMM were employed using appropriate parameters. Data from these complementary analyses were merged to produce a non-redundant reference gene set using GLEAN [58]. In addition, RNA-Seq data from multiple tissues (young roots, leaves, flowers, developing seeds, and shoot tips) from our previous study [17] were also incorporated to aid in gene annotation. RNA-Seq data were mapped to the assembled genome using TopHat [59], and transcriptome-based gene structures were obtained by cufflinks [60]. Then, we compared this gene set with the previous one to get the final non-redundant gene set of sesame (Tables S8 to S10 in Additional file 1). The non-coding gene predictions and gene function annotations were conducted as described in Supplementary Note 3 and Table S11 in Additional file 1.

Repeat annotation

We identified repeat content in the sesame genome using a combination of de novo and homology-based approaches (Supplementary Note and Tables S12 and S13 in Additional file 1). Full-length LTR retrotransposons were identified by LTR_STRUC [61] and classified as Gypsy, Copia and other types of transposons using the program RepeatClassifer implemented in the RepeatModeler package [62]. Then the insertion time of LTR retrotransposons was dated according to the method described by JessyLabbé [63] (Supplementary Note and Figure S8 in Additional file 1).

Evolution analysis

Gene clustering was conducted with OrthoMCL [64] by setting the main inflation value to 1.5 and other parameters as default. PHYML [65] was selected to reconstruct the phylogenetic tree based on the HKY85 model [66]. The program MCMCTree of the PAML package [67] was used to estimate species divergence time. Mcscan [68] was used to construct chromosome collinearity. Detailed descriptions about the identification of recent WGD events and two subgenomes are provided in Supplementary Note 4 in Additional file 1.

Analysis of resistance genes in sesame

HMMER V3.0 [69] was used to screen the predicted sesame proteome against the raw hidden Markov model corresponding to the Pfam NBS (NB-ARC), and further build a sesame-specific NBS hidden Markov model for screening. The TIR and LRR domains were identified using local Pfam_Scan (-E 0.01 --domE 0.01). MARCOIL [70] with a threshold probability of 90 and the program paircoil2 [71] with a P-score cutoff of 0.025 were used as the settings for the CC motif identification.

The absence of NBS genes with a TIR domain in the sesame genome was further validated by checking the gene-masked assembly and the unassembled reads. For the masked assembly, we found nine NB-ARC fragments (>300 bp), but no TIR hit was obtained. Among all the unmapped reads, only 19 showed homology to the TIR domain, but all the reads together covered less than half of the TIR region. Considering the above results, NBS genes with a TIR domain were absent from sesame (for detailed methods see Supplementary Note 5 in Additional file 1).

Analysis of important characteristics in the genome

The homologous lipid genes in sesame and other crops were identified by blastp (1e-5, identity >30%) based on the database of acyl-Lipid metabolism in A. thaliana[72] (for detailed methods see Supplementary Note 7 in Additional file 1).

Genome resequencing and SNP calling

For each accession, a paired-end sequencing library with insert sizes of 500 bp was constructed and then sequenced on the Hiseq 2000 platform. The raw reads were then subjected to a series of stringent filtering steps that had been used in de novo genome assembly (Supplementary Note 1.3 in Additional file 1). Finally, we generated a total of more than 120 Gb clean data with each sample at over 13-fold sequence depth (Data S11 in Additional file 2). The clean reads were mapped to the assembled sesame genome using BWA software [73]. After mapping, SNPs were identified with read mapping quality ≥20 on the basis of the mpileup files generated by SAMtools [74] (Data S7 in Additional file 2). The SNPs extracted by the above process were first filtered by the sequencing depth: ≥30 and ≤581 using the vcfutils program in SAMtools. Then the raw SNP sites were further filtered using the following criteria: copy number ≤2 and a minimum of 5 bp apart with the exception of minor allele frequencies (≥0.05), whereby SNPs were retained when the distance between SNPs was less than 5 bp. Diversity parameters π and θ w were measured using a window of 10 kb with a step of 1 kb [43, 45].

Detection of copy number variations was performed as described by Zheng et al.[75] and Jiao et al. [76] (Supplementary Note 8 in Additional file 1).

Data access

Genomic data generated by the whole project are available at NCBI under accession number APMJ00000000 [77]. WGS raw reads are deposited under the SRA study: SRA122008 [78]. The raw RNA-Seq data are deposited under the SRA study: SRA122023 [79]. Genome assembly, annotation and RNA-Seq data are also available at [80].

Watch the video: Classification (February 2023).