Bacillus cereus, Listeria monocytogenes, and Enterococcus faecium in different growth phases.Bacterial proteases are implicated in protein quality control, biofilm formation or might have a direct function in pathogenesis by processing virulence factors or cleaving host factors. In recent years, knowledge of proteases expressed by Gram-negative pathogens remarkably increased. However, investigation of proteases from Gram-positive bacteria is rather rare, but required for the analysis of pathogenesis-relevant proteases. In this study, we extracted and detected proteases from the gastrointestinal pathogens Bacteria were grown to logarithmic or stationary phases, harvested and extracted by sonication and French press. For the detection of active proteases, zymography analyses were performed using casein and gelatin as substrates to monitor caseinolytic and gelatinolytic activities.B. cereus and distinct caseinolytic proteases exhibiting molecular weights of > 170 kDa, 70 kDa and 45 kDa were shown in L. monocytogenes and E. faecium, respectively. Interestingly, detected proteases were differentially regulated in bacteria grown to logarithmic or stationary phases.We observed different active proteases with different intensities in bacteria grown to logarithmic or stationary phases. Strong activities as gelatinases were detected in B. cereus, L. monocytogenes, and E. faecium, which might contribute to bacterial pathogenesis.In summary, the data clearly indicated proteases that are differentially regulated in the Gram-positive pathogens  Functionally, these proteases play important roles in protein quality control, stress tolerance, replication or in the presentation of virulence factors and have often been described as indispensable factors for normal bacterial growth or virulence [Regulated proteases are implicated in many bacterial processes including growth, motility, biofilm formation, modulation of host responses, etc. . Investietc. ,3. Theseetc. , which cetc. . Promineirulence . TherefoHelicobacter pylori (H. pylori) and Campylobacter jejuni (C. jejuni) by casein zymography followed by mass-spectrometry analyses [H. pylori and C. jejuni secrete HtrA that directly interferes with host cell functions by cleaving the cell adhesion protein E-cadherin on epithelial cells. Consequently, HtrA activity allows migration of bacteria across an intact epithelium [Escherichia coli (EPEC) and Shigella flexneri [H. pylori HtrA serves as a paradigm of a direct protease-mediated interference with pathogenesis of Gram-negative pathogens. Nevertheless, investigation of bacterial proteases is still at the very beginning and the identification of proteolytically active proteins might improve the understanding of complex pathogen-host interactions or tolerance against stress during infection. In particular, proteases expressed by Gram-positive pathogens causing gastrointestinal disorders, such as Enterococcus faecium (E. faecium), Listeria monocytogenes (L. monocytogenes) or Bacillus cereus (B. cereus) have not been investigated yet.In our previous studies, we identified the bacterial ATP-independent chaperone and serine protease HtrA as an active protease expressed in the periplasm of analyses ,8. H. pyithelium ,9 indicaflexneri  pointingetc. In zymography analyses, proteases can be detected as clear bands in substrate-containing gels after denaturing SDS-PAGE separation under non-reducing conditions, renaturation and protein staining [E. faecium, L. monocytogenes and B. cereus. Proteases have been examined for caseinolytic and gelatinolytic activities to obtain more information on the expression of bacterial proteases, which might exhibit important roles in viability and/or pathogenesis.Individual proteases from Gram-negative bacteria are easily detectable by zymography using different substrates, such as gelatin, casein, staining . TherefoL. monocytogenes  was cultivated in Luria-Bertani (LB) broth. B. cereus (ATCC 14579) was grown in nutrient broth. For E. faecium (ATCC 6057) columbia agar containing 5% sheep blood  or brain-heart-infusion (BHI) medium  were used. All bacteria strains (600 of approximately 0.8 (logarithmic phase). Bacterial cultures were centrifuged at 4500 × g for 20 min at 4°C. Pelleted bacteria were then harvested in PBS  or lysis buffer . Where indicated 5 μg/ml lysozyme  was added for 1 h at 37°C. Bacteria suspended in PBS or lysis buffer were sonicated on ice 3 times for 45 sec with 50 % power. All bacterial lysates were centrifuged at 16000 × g for 20 min at 4°C. The protein content of the lysates was measured using Bradford protein assay . All experiments were repeated at least four times. strains  were culFor the disruption of bacteria by French pressure cell press , equal numbers of bacteria were harvested in PBS containing 5 μg/ml lysozyme as indicated. A volume of 10 ml suspension was filled in a 20k Manual-Fill cell. The French press was operating with 11000 psi as maximal pressure. Two cycles were performed for every sample.Protein lysates were separated using SDS-PAGE. All samples were incubated with non-reducing sample buffer (125 mM Tris-HCl (pH 6.8), 20% glycerin, 4% SDS, 0.02% bromophenol blue) for 20 min at room temperature. 10 μg protein of all samples were loaded onto the gels. Gels were stained with Coomassie Blue G250 .B. cereus), 10 μg (E. faecium) or 20 μg (L. monocytogenes) protein was analyzed by zymography using 0.1 % casein or 0.1 % gelatin as substrates under non-reducing conditions as described before [p ≤ 0.001, **p ≤ 0.01 and *p ≤ 0.05 were considered statistically significant.5 μg  from L. monocytogenes was detected (L. monocytogenes has not been detected under these conditions (E. faecium. In E. faecium lysates obtained by all tested methods, casein-degrading activities of > 170 kDa and about 45 kDa were observed, but no gelatin-targeting proteases (Lysates of L. monocytogenes grown to the stationary phase was set as 1 and compared with the corresponding activity of bacteria in the logarithmic phase. The four gelatinolytic activities from B. cereus were collectively quantified. For the quantification protease activities of B. cereus and E. faecium, extracts obtained by French press were included, while caseinolytic activities in lysis buffer-extracted L. monocytogenes were quantified. As previously indicated, no caseinolytic proteases were detected in B. cereus in the logarithmic phase as well as at the stationary phase (B. cereus grown to the stationary phase (B. cereus was more than 90% down-regulated in the bacteria grown to the stationary phase compared to bacteria in the logarithmic growth phase (L. monocytogenes. Here, a casein-degrading protease of approximately 70 kDa was clearly detectable in bacteria grown to the stationary phase, which were extracted by sonication in lysis buffer. This protease was less visible after disruption of bacterial cultures in the stationary phase by French press or sonication in PBS without detergents (E. faecium contained differentially regulated proteases as shown in the casein zymogram. Both, the ~45 kDa and >170 kDa protease were active in bacteria in the logarithmic phase, but significantly decreased in the stationary phase. Obviously, E. faecium in the stationary phase were only poorly disrupted by sonication, but equally efficient by the French press method as implied by the background detection of proteins (E. faecium. Here, a 90% and a 50% reduction were detected for the > 170 kDa and the 45 kDa activities, respectively (Expression of proteases and regulated proteolysis can also depend on bacterial growth phases allowing specific adaptions of bacteria to a changing environment  and bactry phase . The gelB. cereus, L. monocytogenes and E. faecium, we detected caseinolytic or gelatinolytic proteases, respectively. Nevertheless, information on those active proteases in Gram-positive bacteria is rare. An unidentified 105 kDa collagenase with unknown function was described in 1999, which exhibited similarities with clostridial collagenases [L. monocytogenes. Here, the 26 kDa serine protease ClpP has been described as an essential factor for the intracellular life of L. monocytogenes in vivo [L. monocytogenes pathogenesis through enhancing its viability under stress conditions [E. faecium, L. monocytogenes and B. cereus, which were differentially regulated in the logarithmic and stationary phase indicating that regulated protease activity is crucially important in a dynamic environment [B. cereus gelatinase was decreased in bacteria grown to the stationary phase. In L. monocytogenes, the high molecular weight caseinolytic protease decreased while a ~70 kDa protease activity strongly increased. In E. faecium, both, the > 170 kDa and ~40 kDa activity was drastically down-regulated in bacteria grown to the stationary phase. This might reflect changing conditions for bacteria requiring enhanced degradation of misfolded protein during protein quality control. In fact, an htrA knock-out mutant of L. monocytogenes showed an impaired biofilm formation supporting the hypothesis that proteases are implicated in bacterial adaptation and development [E. coli, proteolytic heat shock proteins were differentially regulated via an alternative sigma factor [L. monocytogenes, differentially expressed proteins, including the protease ClpB, have already been identified [B. cereus and E. faecium, those studies are not available yet, but our data imply that proteases are differentially regulated in these pathogens.In the last years, proteases originating from bacterial pathogens received increased attention as it became clear that proteases are implicated in pathogenesis via direct and indirect mechanisms. The majority of studies was performed in Gram-negative pathogens; hence, it was tempting to analyze proteases expressed by Gram-positive pathogens by zymography. We used different methods for efficient extraction of proteases. In fact, sonication in nonionic and anionic detergent-containing lysis buffer was a simple and rapid method for bacterial disruption leading to an enhanced solubility of cytoplasmic and membrane-located proteases. Generally, proteases belong to a large and very complex group of enzymes that considerably differ in structure, substrates, and catalytic mechanism. In agenases . Bacteriagenases  and are  in vivo  and it w in vivo ,18. As anditions . In Entenditions . Althougironment . The strelopment . In E. ca factor  allowingentified ,24. For B. cereus, L. monocytogenes and E. faecium in zymography analyses. Active proteases degraded casein or gelatin as substrates and were differentially expressed or regulated in growing and starving bacteria. Although the proteases were not identified yet, we assume that they might play a functional role in bacterial survival, biofilm formation or pathogenesis by targeting intracellular misfolded proteins, and/or extracellular matrix proteins. Because B. cereus, L. monocytogenes, and E. faecium are disease-relevant pathogens of the gastrointestinal tract, we assume that improved knowledge of stress-and/or density-regulated protease activity could also be important in clinical practice. Further research is necessary to characterize these proteases as putative pathogenic or virulence factors.In this study, we detected proteolytic proteins expressed by the gastrointestinal pathogens


Staphylococcus aureus is a successful human and animal pathogen. The majority of infections caused by this pathogen are life threatening, primarily because S. aureus has developed multiple evasion strategies, possesses intracellular persistence for long periods, and targets the skin and soft tissues. Therefore, it is very important to understand the mechanisms employed by S. aureus to colonize and proliferate in these cells. The aim of this review is to describe the recent discoveries concerning the host receptors of nonprofessional phagocytes involved in S. aureus internalization. Most of the knowledge related to the interaction of S. aureus with its host cells has been described in professional phagocytic cells such as macrophages. Here, we showed that in nonprofessional phagocytes the α5β1 integrin host receptor, chaperons, and the scavenger receptor CD36 are the main receptors employed during S. aureus internalization. The characterization and identification of new bacterial effectors and the host cell receptors involved will undoubtedly lead to new discoveries with beneficial purposes. Staphylococcus is a Gram-positive commensal and opportunistic human pathogen that causes serious community-acquired and nosocomial infections, including abscess formation, wound infection, endocarditis, osteomyelitis, pneumonia, and sepsis/septic shock [ S. aureus cause diseases in cattle (mastitis), poultry, pigs, and horses [ic shock , 2. Addid horses , 4. Tread horses . S. aureus have the ability to invade and persist within nonprofessional phagocytic cells (NPPCs), such as epithelial [Evidence exists that several strains ofithelial –8, endotithelial , 10, ostithelial , 12, fibithelial , 14, andithelial , 16. Thiithelial , 18 and  S. aureus to accomplish bacterial internalization. Finally, we will discuss the medical implications derived from this knowledge and show a summary of the host receptors related to S. aureus internalization in NPPCs in Several reviews have discussed the intracellular persistence of this bacterium , the rolBacterial internalization is a strategy that allows bacteria to evade the host immune response and to survive in the host cells. Several bacteria require initial adhesion to the host cell before the internalization process. Therefore, the adhesion and invasion into eukaryotic cells are major steps in bacterial pathogenesis . Listeria spp. [ Yersinia spp. [ Neisseria gonorrhoeae [ S. aureus) [Bacteria are capable of adhering to extracellular matrix components ) through protein-protein interactions mediated by “microbial surface components recognizing adhesive matrix molecules” (MSCRAMMs) or “secreted expanded repertoire adhesive molecules.” Additionally, bacterial adhesins recognize host cell surface elements such as integrins, cadherins, and selectins . Pathogeria spp. , Yersininia spp. , 39, andorrhoeae , and (2) aureus) , 41.The bacterial engagement of eukaryotic receptors such as integrins often triggers a receptor-mediated internalization process that facilitates access to a protected intracellular niche, promoting bacterial replication , 42.S. aureus possesses a wide arsenal of virulence factors  that contribute to the pathogenesis of infection  [ S. aureus expresses adhesins such as fibronectin-binding proteins (FnBPs), fibrinogen-binding proteins, elastin-binding proteins, collagen-binding proteins, clumping factor, extracellular adhesion protein (Eap), and protein A [ S. aureus also possesses other cell-associated components such as capsular polysaccharide, peptidoglycan (PGN), and lipoteichoic acid (LTA) and secretes components such as enzymes  and toxins , which are very important for the establishment of infection [ S. aureus components and their cognate receptors in NPPCs that lead to bacterial internalization.i, 2013) . These ci, 2013) . S. aurerotein A –45. S. anfection , 46. In α- and β- subunits [α- and 8 β-subunits have been described [β1 integrin mediates adhesion and endocytosis of Yersinia [ S. aureus [ S. aureus in NPPCs is shown in Integrins are cation-dependent glycoprotein transmembrane receptors containing noncovalently associated subunits . In vertescribed . Integriescribed , 48. TheYersinia  and S. a. aureus , 41. Thi. aureus , 50. The S. aureus. This bacterium expresses two closely related FnBPs encoded by the genes fnbA and fnbB [Fn is a key dimeric glycoprotein in the extracellular matrix. The ability to bind to Fn is a characteristic of bacterial adhesion, which is a well-known mechanism described for many pathogens, includingand fnbB , which aand fnbB . S. aureus adhesion and internalization via a zipper-like process in NPPCs are mediated by integrins, Fn, and FnBPs. The role of FnBPs during S. aureus invasion has been established in endothelial cells [α5β1 or anti-Fn antibodies. The results of these approaches showed that FnBPA has a relevant role in invasion because its deletion in the S. aureus Cowan strain diminished the level of invasiveness (~80%) into a human embryonic kidney cell line (HEK 293) [ S. aureus (8325-4) that does not express FnBPs showed reduced internalization into transformed bovine mammary epithelial cells (MAC-T cells) [ S. aureus confers the advantage for tissue colonization in vivo, as observed in mammary glands, and confers the induction of severe infection [Since the 1980s, it has been well recognized thatal cells , osteoblal cells , keratinal cells , 55, fibal cells , and epial cells , 22. TheHEK 293) . SimilarT cells) , and kerT cells) . The rolT cells) . The prenfection , 59. In  S. aureus Cowan and P1 strains, presumably by competing with the S. aureus FnBP to interact with the host cell receptor [ S. aureus internalization in other cell types, for example, endothelial cells [ S. aureus FnBPs with NPPCs.In contrast, the role of Fn was initially elucidated in HEK 293 cells. The preincubation of these cells with a soluble recombinant protein fragment composed of the Fn-binding domain of FnBP completely abolished the invasion byreceptor . The useal cells , 24. The S. aureus internalization into NPPCs has been demonstrated by blockage experiments with antibodies. The blockage of integrin α5β1 by specific antibodies in HEK 293 [ S. aureus internalization because their blockage leads to a significant reduction of internalized bacteria. Additionally, a monoclonal antibody specific for β1 integrins dramatically reduced S. aureus invasion into human Hep-2 cells [β1 integrin showed significantly reduced bacterial invasion [α5β1 are crucial for S. aureus invasion in different epithelial cells [β1 integrin ligands, has demonstrated the role of integrin during the internalization of S. aureus into alveolar epithelial cells (A549) by reducing the number of CFU recovered. In this work, the siRNA-mediated knockdown of β1 integrin expression in A459 cells significantly reduced S. aureus internalization (~50%) [ S. aureus internalization into primary bovine mammary epithelial cells [The role of integrins during HEK 293 , in HUVE HEK 293  cells, o HEK 293  demonstr-2 cells . In addiinvasion . Recent al cells . The usen (~50%) . In addial cells . S. aureus FnBPs and α5β1 integrin are necessary for efficient S. aureus internalization into NPPCs; however, other mechanisms are employed by this bacterium favoring its internalization that we will describe below.Overall, these results strongly suggest thatHeat shock proteins (Hsps) are a group of evolutionarily highly conserved molecules that are expressed by prokaryotic and eukaryotic cells. These proteins perform important intracellular functions regarding protein folding and transport . S. aureus internalization into NPPCs was first reported by Dziewanowska et al. (2000) [ S. aureus internalization. Another Hsp related to S. aureus internalization in NPPCs is Hsc70. This protein is associated with viral infections by acting as a receptor for human T-cell lymphotropic virus type 1 (HTLV-1) [ S. aureus hydrolases such as autolysin (Atl) during the bacterial internalization process. Atl participates in biofilm formation and mediates binding to the extracellular matrix and plasma proteins [ atl-deficient S. aureus mutant SA113atl strain for its capability to be internalized into endothelial cells, and they showed the impaired ability of this strain to be endocytosed by these host cells [ S. aureus internalization in these cells, and this protein has also been involved during Brucella abortus invasion into trophoblast giant cells [The role of Hsps during. (2000) . Using a(HTLV-1)  or rotav(HTLV-1) , 66. Hscproteins , 67, 68.st cells . Additiont cells , which sκB [TLRs offer an efficient and immediate response to bacterial, fungal, and viral infections by recognizing PAMPs. The TLR family consists of 13 mammalian members, and each member mediates an intrinsic signaling pathway and induces specific biological responses against microorganisms . The cytκB . The leuκB . TLRs ar S. aureus infections, TLR2 is the most relevant receptor involved in this process. TLR2 recognizes different PAMPs such as lipopeptides from Gram-positive and Gram-negative bacteria, lipoarabinomannan, LTA, PGN, atypical lipopolysaccharide, a phenol-soluble modulin from S. epidermidis, and others [ S. aureus internalization in NPPCs; however, the results are not conclusive because TLR2 participation in phagocytosis may be indirect. For example, Rocha-de-Souza et al. (2008) indicated that TLR2 is involved in S. aureus internalization into human cord blood-derived mast cells using neutralizing antibodies [ per se, they are also internalized in the process and participate in the link between phagocytosis and inflammatory responses by triggering the production of cytokines [ S. aureus PAMPs. In NPPCs, the predominant triacylated lipoprotein of S. aureus, SitC, is located intracellularly with TLR2 in murine keratinocytes and stimulates proinflammatory cytokine expression [ S. aureus internalization, this process appears to be a prerequisite for full TLR2 activation in both professional phagocytic cells as well as in NPPCs [Ford others . Additiod others  and a did others , while td others . Reportstibodies . The bloytokines . In addipression ; howeverin NPPCs . S. aureus mediated by TLR2, CD36 may act as a facilitator or coreceptor for diacylglyceride recognition through the TLR2/6 complex mediating bacterial invasion primarily in phagocytic cells [ S. aureus, suggesting a role for CD36 during the endocytosis of Gram-positive bacteria [ S. aureus colocalizes with CD36 in HeLa cells [ S. aureus internalization; however, this effect remains to be fully explored.CD36 is a membrane glycoprotein that belongs to the class B scavenger receptor family that interacts with other membrane receptors such as TLRs. This receptor plays a role during tumor growth, inflammation, wound healing, and angiogenesis and is able to recognize PAMPs or pathogen-infected cells by acting as a phagocytic receptor , 79. Duric cells . In the bacteria . In addiLa cells . CD14, aLa cells . CD14/TLLa cells . CD14 anLa cells . The afo S. aureus to invade NPPCs  iny factor , and cautination . This pral cells  and fibral cells . Eap alsal cells , while tlization , 86. Thilization ; however S. aureus colonization and internalization [ S. aureus has two GAPDH homologs termed gapA  and gapB [ S. aureus in a Galleria mellonella model of infection [Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is a glycolytic enzyme, and several GAPDH homologs present in bacteria are able to bind to Fn, lysozyme, plasminogen, and the cytoskeletal proteins myosin and actin. Therefore, this enzyme plays a role duringlization , 89. S. and gapB , and botnfection .GapC plays an important role during S. aureus internalization into MAC-T cells [ gapC mutant H330 strain that were adhered and internalized into MAC-T cells was lower than the number corresponding to the WT strain. Nevertheless, the absence of gapC does not completely abolish the attachment and internalization of the bacteria, which is most likely due to the presence of other bacterial adhesins [ gapC.-T cells . The numadhesins . No repoS. aureus acquires iron from host hemoglobin due to the bacterial expression of iron-regulated surface determinants (Isd) [ S. aureus into 293T and HeLa cells [ S. aureus IsdB binds to and stabilizes the active conformation of integrins, enabling them to interact with RGD-containing ligands, which leads to bacterial internalization in an integrin-dependent pathway. In addition, IsdB adheres to platelets through the integrin receptor GPIIb/IIIa (aIIIbb3) [ts (Isd) . ZapotocLa cells . AdditioaIIIbb3) ; however S. aureus ( S. aureus) are chronic and recurrent, and many of them are life threatening.Phagocytosis is an essential component of innate and adaptive immune responses. In NPPCs, phagocytosis plays major roles in tissue maintenance, regeneration, and remodeling. However, pathogenic bacteria also employ many of the receptors involved in phagocytosis during the interplay between the host cell defense response and tissue colonization. Thus, phagocytosis, endocytosis, and intracellular trafficking can be exploited for therapeutic objectives such as intracellular drug delivery  . In addi. aureus  because


Amblyomma triste, A. cajennense and A. parvum ticks are very important in veterinary and human health because they are vectors of the etiological agents for several diseases. Insights into the tick salivary components involved in blood feeding are essential to understanding vector-pathogen-host interactions, and transcriptional profiling of salivary glands is a powerful tool to do so. Here, we functionally annotated the sialotranscriptomes of these three Amblyomma species, which allowed comparisons between these and other hematophagous arthropod species.Tick salivary constituents antagonize inflammatory, immune and hemostatic host responses, favoring tick blood feeding and the establishment of tick-borne pathogens in hosts during hematophagy. A. triste, A. cajennense and A. parvum ticks fed on different host species were pyrosequenced on a 454-Roche platform to generate four A. triste  libraries, one A. cajennense  library and one was A. parvum  library. Bioinformatic analyses used in-house programs with a customized pipeline employing standard assembly and alignment algorithms, protein databases and protein servers.mRNA from the salivary glands of A. triste, A. cajennense and A. parvum ticks produced 11,240, 4,604 and 3,796 CDSs, respectively. These CDSs were classified into over 100 distinct protein families with a wide range of putative functions involved in physiological and blood feeding processes and were catalogued in annotated, hyperlinked spreadsheets. We highlighted the putative transcripts encoding saliva components with critical roles during parasitism, such as anticoagulants, immunosuppressants and anti-inflammatory molecules. The salivary content underwent changes in the abundance and repertoire of many transcripts, which depended on the tick and host species.Each library yielded an average of 100,000 reads, which were assembled to obtain contigs of coding sequences (CDSs). The sialotranscriptome analyses of Amblyomma species. These comprehensive databases will be useful for the characterization of salivary proteins and can be applied to control ticks and tick-borne diseases.The annotated sialotranscriptomes described herein richly expand the biological knowledge of these three The online version of this article (doi:10.1186/1756-3305-7-430) contains supplementary material, which is available to authorized users. Arthropods have developed several feeding habits during the course of evolution, and within this taxa, hematophagy evolved independently over millions of years, resulting in significant differences among hematophagous arthropods , 2. MostAmblyomma (Acari: Ixodidae) , for A. parvum [GenBank: GBBL01000001 - GBBL01002838 (BioProject 241271)] and A. cajennense .Sequence deposition for The experiments were approved by Animal Experimentation Ethics Committee of the Federal University of Uberlândia, protocol #033/14, according to Ethical Principles on Animal Research of the National Council for the Control of Animal Experimentation (CONCEA).Amblyomma genus, obtained from six 454-based RNA-seq libraries: one library from A. parvum female ticks fed on dogs, one library from A. cajennense female ticks fed on rabbits and four libraries from A. triste ticks. The sialotranscriptome of the latter species addressed different parasitological conditions including the developmental stage of the tick, the type of host that each stage prefers [We generated and analyzed the transcriptional profile of salivary glands (SG) from three neotropical hard ticks belonging to the  prefers  and the A. parvum library yielded 243,567 pyrosequencing reads, and the A. cajennense yielded library 67,677 pyrosequencing reads. The four combined A. triste libraries yielded 1,195,924 pyrosequencing reads (data not shown). Only the pyrosequencing reads longer than 149 nucleotides were used to assemble primary contigs. The primary assembled contigs (minimum of 3–4 reads per contig) were analyzed to extract putative CDS, and the CDS contigs were used to annotate each sialotranscriptome. The CDS contigs, categorized according to their putative function, were plotted in hyperlinked Excel spreadsheets available as additional files for download: A. triste  for NGP1, 7,391 CDS contigs  for NGP2, 9,311 CDS contigs  for FD1 and 9,004 CDS contigs  for FD2. Together, A. triste libraries produced a total of 11,240 CDS from 442,756 reads  Housekeeping, constitutive genes required for the basal maintenance of tissues; c) Unknown and d) Unknown Secreted, which had non-significant BLAST hits or no matches against any database, being that the latter category (d) contained signal peptide sequences; e) Transposable Elements, mobile elements in genomes; f) Viral, transcripts with similarities to viral proteins and g) Leishmania-related, transcripts with similarities to Leishmania proteins. These data are numerically summarized in Table Transcripts in the three sialotranscriptomes were classified into seven main categories: a) Unknown and Unknown Secreted categories together presented an average of 13% of reads, and this relatively low proportion is a consequence of previous efforts to describe transcripts in salivary glands from several tick species [On average, 20% of the reads in the three sialotranscriptomes were annotated as putative secreted proteins, whereas the majority of the reads (ranging from 62.9% to 68.9%) were annotated as housekeeping genes Table . The Unk species .Amblyomma ticks are vectors of several microorganisms that are important public health threats, we examined the sialotranscriptomes for CDS related to microbes. The A. triste and A. cajennense sialotranscriptomes contained 10 and 6 CDSs, respectively, that matched viral-like proteins  that was primarily annotated as ferredoxin protein and that best matched Rickettsia sibirica  were shared within all 47 reads Secreted and Housekeeping categories contained several functional subcategories, and most of these were common between two or three sialotranscriptomes. To understand how the transcriptional profile of these different functional subcategories changes across the three Amblyomma species, we performed a hierarchical clustering using the abundance of transcripts (relative percentage of reads) for each sialotranscriptome. For the A. triste sialotranscriptome, we deconstructed it according to the experimental conditions .The expression data are displayed as heatmaps where the black to red colors indicate low and high expression levels, respectively  or females fed on dogs (FD)  might have been influenced by the blood meal source for this tick, which was fed on rabbits (FR). Almost all A. cajennense transcript families had lower expression compared with the other libraries. These transcription profiles suggest that the amount and content of proteins produced by salivary glands depends on the tick species and life stage as well as the host background.Regarding the clustering of Secreted category contained about one-fifth of the transcripts  as well as the different host environments .The hierarchical clustering of the putative secreted transcripts resulted in distribution pattern similar to housekeeping protein families, such that A. cajennense and the A. parvum and A. triste libraries  contained significantly less GRP transcripts than A. parvum females and A. triste fed on dogs . Members of this family are abundant in the sialotranscriptomes of hematophagous arthropods, such as flies and ticks , 77, 78,me Table . In all m Figure . This fian hosts : whilst A. triste libraries , and the expression of other lipocalins was significantly higher in A. parvum compared with A. cajennense and A. triste females  were more abundant in n dogs FD and FD2,tus tick , and tratus tick , 39, 43.Amblyomma genus, namely, A. maculatum[A. variegatum[Amblyomma genus—for example, Amblin [A. triste sialotranscriptome (At-143156), and we found sequences in the sialotranscriptome of A. triste  and A. cajennense (Ac-23315) annotated as serpins with at least 82% of amino acid identity with the serpins/lospins from A. americanum[A. hebraeum— were also presented in A. parvum  and A. cajennense . Protein sequence similarities with other Amblyomma species can be explored in the three annotated sialotranscriptomes  were compared to determine which transcripts were shared and unique in these four libraries . Both transcripts were highly expressed in the nymphal stage, which had 10-to-20-fold more reads than the female libraries , suggesting that both the life stage and host may be driving gene expression in salivary glands.A. cajennense female ticks have been the subject of two other gene expression studies, conducted by Batista et al.  in the RNA-seq (454) and LIBEST_019946 overlap, secreted proteins were the majority of sequences (52.4%) shared by the RNA-seq (454) and LIBEST_USPRP overlapping reads  domains within its 445 amino acids (aa). A five-KU domain protein, Penthalaris, is a tick anticoagulant found in the salivary glands of the Lyme disease vector, Ixodes scapularis[In addition to its 70% novel sequences  domains and inhibit either cysteine or cation-dependent proteinases [A. triste, A. parvum and A. cajennense sialotranscriptomes contained 11 full-length thyropin sequences that were compared with other 15 thyropin sequences from A. maculatum, A. variegatum, Ixodes ricinus, Rhipicephalus pulchellu s, R. sanguineus and Ornithodoros moubata ticks  presented low similarity with proteins from hard ticks and clustered as an external group. Two robust super clades (defined by related proteins belonging to clades with > 86% bootstrap support) were composed of three polyspecific clades (with > 72% bootstrap support). Most Amblyomma thyropins are more closely related to each other, and some species-specific thyropin sequences were very similar , which could represent alleles from the same gene or products of gene duplication. Thyropin sequences found in A. triste and A. cajennense clustered in clade I and presented higher similarities with Rhipicephalus sequences than with proteins in clade IV, which is composed of sequences from all three Amblyomma sialotranscriptomes. We observed two consistent subclusters in clade I and IV, formed by A. triste and A. maculatum sequences, which corroborated the close relationship between these tick species previously described by Estrada-Peña et al. [Amblyomma thyropins in clades I and IV is reflected in features such as potential glycosylation sites. A detailed analysis of A. cajennense thyropin sequences (performed by the NetOGlyc 4.0 Server) demonstrated that CDS Ac-36285 has one and Ac-103065 has no potential glycosylation sites, while Ac-50867 has 32 potential glycosylation sites . Notably, clade VIII indicated an earlier deviation of I. ricinus DAP-36 proteins from other members of the Ixodidae family. As with thyropins, ticks may have developed DAP-36 immunosuppressant proteins through gene duplication, and members of the same clade might have similar functions. Interestingly, CDS Ap-15676 showed little similarity to other Amblyomma sequences and was clustered as an external group, suggesting that DAP-36 proteins are divergent within the Amblyomma genus. Based on sequences that are >20% divergent at the amino acid level, three putative genes in A. triste and A. parvum and two putative genes in A. cajennense encode members of this family.Immune modulation is an important requirement for tick feeding because contact with hosts leads to the recognition of tick antigens by immune cells and subsequent activation of both cellular and humoral responses. Suppression of the immune system of hosts facilitates feeding and creates a convenient microenvironment for enhanced pathogen transmission . Ticks dy glands . Fifteeni Figure . AlthougA. parvum and A. triste, which are reported reservoirs and potential vectors of pathogenic agents such as Rickettsia. Additionally, we obtained a larger and more accurate sialotranscriptome of the vector of Brazilian spotted fever, the A. cajennense tick. This work extensively supplements the current biological knowledge of the Amblyomma genus through the tens of thousands of sequences deposited and freely available for further characterization. Transcripts encoding the protein families important for tick-host-pathogen interactions were common among the libraries and shared similarities with other heteroxenous hard ticks. Thus, these components are good targets for controlling tick infestations and, consequently, decreasing the incidence of tick-borne diseases.We generated the first detailed transcriptional profile of salivary glands from two important hard ticks from South America, All authors were members of a collaborative effort, the GENOPROT: Research Network in Ticks, which was sponsored by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and whose aim was to study the transcriptome and proteome of tick species important for public health and livestock in Brazil. Except for LGG, MMM and HNSM, who have the MSc title, all other authors have the PhD title. SRM is a postdoctoral fellow supported by the São Paulo Research Foundation .AF1. Annotated sialotranscriptome of the Amblyomma triste tick (.xlsx), available at http://exon.niaid.nih.gov/transcriptome/sm/AF1-Atris-web.xlsx(DOCX 31 KB)Additional file 1: AF2. Annotated sialotranscriptome of the Amblyomma parvum tick (.xlsx), available at http://exon.niaid.nih.gov/transcriptome/sm/AF2-Aparv-web.xlsx(DOCX 32 KB)Additional file 2: AF3. Annotated sialotranscriptome of the Amblyomma cajennense ticks, available at http://exon.niaid.nih.gov/transcriptome/sm/AF3-Acaj-web.xlsx(DOCX 31 KB)Additional file 3: Additional file 4: AF4. Functional classification of the LIBEST_USP-RP dataset. (DOCX 26 KB)Additional file 5: AF5. Accession numbers of the public sequences from other ticks used in phylogenetic analyses. (DOCX 26 KB)


To date, more than 125 species of nontuberculous mycobacteria (NTM) have been identified. In this study, we investigated the frequency and clinical implication of the rarely isolated NTM from respiratory specimens.Mycobacterium avium, M. intracellulare, M. abscessus, M. massiliense, M. fortuitum, M. kansasii, M. gordonae, and M. peregrinum. Clinical, radiographic and microbiological data from patients with rare NTM were reviewed and analyzed.Patients with NTM isolated from their respiratory specimens between July 1, 2010 and June 31, 2012 were screened for inclusion. Rare NTM were defined as those NTM not falling within the group of eight NTM species commonly identified at our institution: M. conceptionense was the most common . The median age of the 68 patients with rare NTM was 68 years, while 39 of the patients were male. Rare NTM were isolated only once in majority of patient . Among the four patients from whom rare NTM were isolated two or more times, only two showed radiographic aggravation caused by rare NTM during the follow-up period.During the study period, 73 rare NTM were isolated from the respiratory specimens of 68 patients. Among these, Most of the rarely identified NTM species were isolated from respiratory specimens only once per patient, without concomitant clinical aggravation. Clinicians could therefore observe such patients closely without invasive work-ups or treatment, provided the patients do not have decreased host immunity towards mycobacteria. Mycobacterium tuberculosis complex and M. leprae. Since the recognition of NTM as possible pathogens in the 1950s [Nontuberculous mycobacteria (NTM) are defined as mycobacteria other than he 1950s , the obshe 1950s -5. This M. fragae and M. paragordonae were identified as recently as 2013 [Presently, more than 125 classes of NTM species have been identified . Further as 2013 ,12.M. avium, M. intracellulare or M. abscessus are well known, those caused by newly recognized and rarely isolated NTM are not yet fully understood. In the present study, we investigated the frequency of rare NTM isolation and the clinical characteristics of patients with rare NTM.Although the clinical characteristics of diseases caused by commonly isolated NTM such as Patients from whom NTM were isolated one or more times from respiratory specimens such as sputum, bronchoscopic wash fluid and bronchoalveolar lavage (BAL) fluid between July 1, 2010 and June 31, 2012 at Seoul National University Hospital, were included in the analysis. Hence, a total of 2556 NTM isolated from 1373 patients during the study period were analyzed retrospectively. The Institutional Review Board of Seoul National University Hospital approved the study protocol and waived the requirement for obtaining patient consent.g for 20 min. The processed sediments were stained using the Ziehl-Neelsen method [M. tuberculosis and NTM were differentiated using the Gen-Probe® method  [16S rRNA, rpoB, and tuf. Polymerase chain reaction (PCR) and subsequent sequence were performed and the resulting sequences were compared with those in the reference database using the basic local alignment search tool (BLAST). Mycobacterial species were identified using the 16S rRNA sequences and the algorithm described in the Clinical and Laboratory Standards Institute guidelines MM18-A [Respiratory specimens were decontaminated with 4% sodium hydroxide (NaOH), homogenized, and concentrated by centrifugation at 3000 × n method . ConcentCA, USA) . Followis MM18-A .M. avium, M. intracellulare, M. abscessus, M. massiliense, M. fortuitum, M. kansasii, M. gordonae and M. peregrinum, which are the eight NTM species commonly identified at our institution.For the purposes of this study, ‘rare NTM’ were defined as NTM species other than Demographic, clinical and radiographic data of the patients from whom rare NTM were isolated were reviewed. Demographic data including age, gender, and smoking habits; past medical history of tuberculosis (TB), measles, pertussis, and sinusitis; comorbidities including malignancy, diabetes mellitus, cerebrovascular disease, rheumatic disease, inflammatory bowel disease, gastroesophageal reflux disease, and underlying lung disease; clinical data for self-reported symptoms; and findings of the physical examinations, were all thoroughly reviewed. The characteristics and distribution of lung lesions were analyzed based on chest computed tomography (CT) by two pulmonologists (J.K. and J.J.Y.), who were aware of the patients’ NTM results. Patients from whom rare NTM were isolated more than once were analyzed separately.M. avium  and M. intracellulare  were the most frequently identified rare NTM species, followed by M. abscessus  were commonly isolated NTM species while the others  were rare NTM. M. conceptionense was the most common , followed by M. chelonae, M. lentiflavum and M. mageritense  were from sputum and three (4.1%) were from bronchoscopic specimens such as bronchial washsing and bronchoalveolar lavage. Among the identified rare NTM, The median age of the 68 patients from whom rare NTM were isolated was 68 years , while 39 (57.4%) were male. Of these patients, 24 (35.3%) had a previous history of TB treatment. The most common underlying diseases were solid organ malignancies including lung cancer , and diabetes mellitus . TNF-α inhibitors were used in two patients and HIV infection was confirmed in one patient. Sputum production  and coughing  were the most common self-reported symptoms. Postnasal drip  and crackles  were the most common findings during physical examination (Table Upper lobes of lung were commonly involved (right upper lobe in 40 patients and left upper lobe in 33 patients). Bilateral lesions were found in 30 patients (44.1%). In 21 (30.9%) patients, three or more lobes were involved. Multiple nodules were the most commonly observed radiographic finding . Bronchiectasis  and cavities  were also commonly observed in radiographic examinations . Initial chest CT showed patterns of bronchiectasis (patient 3), small nodules , consolidations (patients 2 and 4), and cavities (patient 4). In one patient  may also cause lung diseases [M. kumamotonense and M. celatum, have generally been considered to be misidentifications or a result of culture contamination, and are thus deemed to be clinically non-pathogenic organisms [Other rare NTM species isolated from patients in the present study . Once-off isolation of the majority of the rare NTM suggests limited clinical significance of these NTM. Additionally, the observation that only one of the three patients from whom rare NTM were isolated two or more times without co-infection with common NTM showed evidence of radiographic aggravation, further substantiates the minimal clinical significance of rare NTM.The limited clinical importance of the frequent one-time isolation of rare NTM presented in this study underscores the importance of the current ATS/IDSA diagnostic guidelines, which require repeated isolation of an NTM in the appropriate clinical setting . CliniciTo fully appreciate these results, a limitation of this study should be noted: species level identification was not performed on all NTM isolated from respiratory specimens. A prospective study including species identification of all NTM isolated during the certain period would likely confirm the findings of the current study.Rarely identified NTM isolated from respiratory specimens have limited clinical importance in most cases. Clinicians who treat patients with rarely identified NTM could therefore observe them closely without any intensive work-ups or treatment being required, provided that these patients do not present with decreased host immunity towards mycobacteria.


A total of 1490, 149 and 83 MITE-related sequences from 89, 17 and five families, respectively, were found in the genomes of the above-mentioned species. Species-specific MITEs are predominant in each genome of microsporidian Nosema, with the exception of three MITE families that were shared by N. bombycis and N. antheraeae. One or multiple rounds of amplification occurred for MITEs in N. bombycis after divergence between N. bombycis and the other two species, suggesting that the more abundant families in N. bombycis could be attributed to the recent amplification of new MITEs. Significantly, some MITEs that inserted into the homologous protein-coding region of N. bombycis were recruited as introns, indicating that gene expansion occurred during the evolution of microsporidia. NbS31 and NbS24 had polymorphisms in different geographical strains of N. bombycis, indicating that they could still be active. In addition, several small RNAs in the MITEs in N. bombycis are mainly produced from both ends of the MITEs sequence.Miniature inverted-repeat transposable elements (MITEs) are short, non-autonomous DNA transposons, which are widespread in most eukaryotic genomes. However, genome-wide identification, origin and evolution of MITEs remain largely obscure in microsporidia. In this study, we investigated structural features for  MITEsnsertion . Abundannsertion , 16. MITnsertion , 18. Tran potato , 19–22. n potato .Nosema bombycis, the earliest identified species of microsporidia, is a fungal pathogen causing pebrine disease, which can lead to devastating economic losses in the silkworm industry. N. bombycis contains large amounts of repetitive elements, which comprise about 25% of the whole genome [Nosema antheraeae is an obligatory parasite to free-range silkworms Antheraea pernyi, and is closely related to N. bombycis [Nosema ceranae is a common pathogen of western honeybee (Apis mellifera), and was thought to be relevant to colony collapse disorder [N. bombycis [piggyBac family NbPB1, Helitron family NbLep1 and Mariner/Tc1 superfamilies [N. bombycis genome, MITEs have destroyed the copy of small ribosomal subunits but are still transcribed together with the latter [Microsporidia are obligate intracellular parasitic fungi that can infect a wide range of organisms, including vertebrates and invertebrates (particularly insects). Some species can cause severe diarrhea, encephalitis and hepatitis in Acquired Immunodeficiency Syndrome (AIDS) patients infected with microsporidia , 25. Nose genome . Nosema bombycis , 27. Nosdisorder . Since tbombycis , a largebombycis , 30–37. families , 33, 38.e latter , indicatN. bombycis and N. antheraeae, as well as their distantly related species, N. ceranae. Classification and polymorphism of MITEs and their roles in genomic evolution are discussed, which could contribute to further understanding of MITE function in microsporidia.In this study, genome-wide identification of MITEs was performed on the whole genomes of microsporidian N. bombycis CQ1 and N. antheraeae YY were freely downloaded from public Silkworm Pathogen Database , or can be downloaded from Genbank (Accession no. ACJZ01000001-ACJZ01003558) and N. ceranae genome was obtained from Genbank accession no.ACOL01000001-ACOL01005465. Considering the genes annotation of N. bombycis and N. antheraeae might exist a potential over-prediction of small genes, re-annotating the genes in N. antheraeae and N. bombycis were fulfilled referring to methods described in previous study [N. bombycis and N. antheraeae was executed as following: CCC-like or GGG-like motifs in the 30 nts upstream and downstream of AUG initiation codons from previous annotation of CDSs were searched to revise the start codons, and then AT content >80% was supplemented as an additional criterion to ensure this revision [N. bombycis and 202 over-prediction genes in N. antheraeae have been rectified and then used in this study. The information of re-annotation genes for N. bombycis and N. antheraeae were both listed in Genomic sequences and gene annotation information of us study . Base onrevision . FinallyN. bombycis involved in this study were kindly provided by Dr Pan Guoqing , Boling Yue, Sericulture Research Institute, Guangxi Province, China), Dr. Qiong yang , Shiliang Chen , which were labeled as strains CQ1, GX, GD and YN, respectively. All four strains were isolated from the local silkworm and reserved in their own labs mentioned above.Four strains of N. bombycis, N. antheraeae and N. ceranae genomes [Based on the structure of MITEs, MITE-Hunter was used to identify MITE candidates from  genomes . MITE-HuStowaway-like, T for Tourist-like, h for hAT-like, Me for Merlin-like, Mu for Mutator-like, and N for others.To mine all the remnant copies of each MITE family, the conserved sequences from each family were used as the query sequence to scan each genome sequence by homology BLAST search. The false results were filtered out based on the criteria of nucleotide identity rate <90% and query coverage <80%. All MITE families were then searched against the RepBase (version 18.05)  and Genbhttp://mfold.rna.albany.edu/). To find small RNAs derived from the MITE transposons, the elements from each MITE family were used as the query sequence to scan the N. bombycis small RNA database by Bowtie2.0, with mismatch <2 [The copy elements of each MITE family were aligned using MUSCLE , and neimatch <2 . These MN. bombycis was explored by MIP analysis. Firstly, orthologous genes between N. bombycis and N. antheraeae were acquired by reciprocal best-hits BLAST. Then, these orthologous genes in a collinear gene order were considered as syntenic regions in respective species. Subsequently, these shared syntenic regions were used to investigate whether there were the shared syntenic regions harboring MITE elements in the N. bombycis, but harboring no MITE elements in the N. antheraeae. Ultimately, eighteen shared syntenic regions where MITEs had inserted in the 5’-flanking regions of orthologous genes from N. bombycis but not inserted in the same region from N. antheraeae were selected as candidates to execute the subsequent PCR analysis (N. bombycis can be judged for the presence/absence of polymorphism due to specific MITEs in those syntenic regions mentioned above. The genomic DNA of the spores was extracted using the CTAB (cetyltrimethylammonium bromide) method. PCR was performed as follows: 5 min at 94 oC, 35 cycles of 95 oC for 40 sec, 53–59 oC (dependent on the primers) for 40 sec, and 72 oC for 1 min, with a final 5-min extension at 72 oC. The PCR products were separated on 1% agarose gels, stained with ethidium bromide and visualized on a UV trans-illuminator.The presence/absence of a MITE in a particular region can produce polymorphism between the relatives, so the different isolates from the same species can be distinguished by MITE insertion polymorphism (MIP) analysis . Accordianalysis . The priN. bombycis were collected for RNA isolation. Following purification, total RNA samples were instantly preserved in ethanol and stored at -80 oC until further use. For deep sequencing, the small RNA samples were prepared as follows: total RNA of each sample was size fractionated on a 15% PAGE gel, and small RNAs around 16–30 nt in length was collected. The 5’RNA adapter (5’-GUUCAGAGUUCUACAGUCCGACGAUC-3’) was ligated to the RNA pool with T4 RNA ligase. Ligated RNA was size fractionated on a 15% agarose gel, and a 40–60 nt fraction excised. The 3’RNA adapter  was subsequently ligated to precipitated RNA using T4 RNA ligase. Ligated RNA was size-fractionated on a 10% agarose gel, and the 70–90 nt fraction  excised. Small RNAs ligated with adaptors were subjected to RT-PCR  to produce sequencing libraries. PCR products were purified and small RNA libraries were sequenced using Solexa, a massively parallel sequencing technology.Silk glands and whole bodies of day-3 fifth instars larvae infected with N. bombycis, N. antheraeae and N. ceranae, respectively. After filtering out false-positive results , 61 (40.9%), 24 (28.9%) of predicted MITEs inserted into gene regions in erformed . HoweverN. bombycis, 21 protein-coding sequences associated with MITEs insertions were targeted to compare the impact of MITEs on gene structure in N. bombycis with their corresponding homologous genes in N. antheraeae  high-quality reads were remained and 6661,609 reads were matched to N. bombycis genomic sequence by Bowtie 2.0 software [N. bombycis by matching all the small RNA tags to the canonical MITEs with Bowtie alignment. About 2,589 non-redundant reads were matched by each MITE family conservative sequence. These MITE-derived small RNAs range from 18–29 nt in length, among which 24–25 nt small RNAs were dominant  gene and therein improve its transcribed level, which lead to the more stable developmental phenotype than that silkworm without the transposon insertion when suffering from food shortage [The link between MITEs distribution and spore traits of the three Nosema species still remained unclear. Recent study reported that in domestic silkworm shortage , 47. So,N. bombycis, since there are many families in this species. Surprisingly, an autonomous hAT-like element encoding an intact transposase was found in N. bombycis, and its TIR sequence is highly homologous to Nbh4 element, which is the most abundant element in N. bombycis. So, it can be hypothesized that the recent amplification of Nbh4 in N. bombycis could have been catalyzed by a hAT-like transposase.Although it was unclear which factors had driven the amplification of MITEs, "genome shock" theory was proposed to explain the amplification of transposons: vast majority of transposons are not active in the evolutionary history, only external stimuli or catalysis through transposase encoded by homologous autonomous transposon will lead to amplification of MITEs , 48. StuN. bombycis genome were predominantly 24 and 25nt long. Moreover, these RNAs were mainly generated in the position of two-terminal sequence, which was similar to the formation of miRNAs. It would be interesting to examine if these MITE-derived small RNAs in N. bombycis were generated by a pathway similar to miRNA or siRNA biogenesis. Likewise, the effect of MITE-derived small RNAs on transposons or genes of N. bombycis deserves further study.Many studies have shown that organisms have a complete mechanism to reduce transposon activity, such as DNA methylation . Recent S1 FigThe positions of designed primers were marked as pair of arrows.(TIF)Click here for additional data file.S2 FigMiS5 and MiS22 have been identified in Solanaceae.MITE families of (TIF)Click here for additional data file.S3 FigGrey rectangle is TSD, black triangles are TIRs, and white rectangles are homologous regions of each transposon in both species. The corresponding names and percentages of identity are shown on the left.(TIF)Click here for additional data file.S4 FigThe copy numbers of identical elements are shown on the left of each sequence. Red arrowheads are TIR.(TIF)Click here for additional data file.S1 File(XLS)Click here for additional data file.S2 File(XLS)Click here for additional data file.S3 File(XLS)Click here for additional data file.S4 File(XLS)Click here for additional data file.S5 File(XLS)Click here for additional data file.S1 Table(XLS)Click here for additional data file.S2 Table(DOC)Click here for additional data file.S3 Table(DOC)Click here for additional data file.S4 Table(XLS)Click here for additional data file.S5 Table(DOC)Click here for additional data file.S6 Table(DOC)Click here for additional data file.


It is released under the liberal Modified BSD open source license, provides a well-documented API in the Python programming language, and is developed by an active, international team of collaborators. In this paper we highlight the advantages of open source to achieve the goals of the scikit-image library, and we showcase several real-world image processing applications that use scikit-image. More information can be found on the project homepage,  In our data-rich world, images represent a significant subset of all measurements made. Examples include DNA microarrays, microscopy slides, astronomical observations, satellite maps, robotic vision capture, synthetic aperture radar images, and higher-dimensional images such as 3-D magnetic resonance or computed tomography imaging. Exploring these rich data sources requires sophisticated software tools that should be easy to use, free of charge and restrictions, and able to address all the challenges posed by such a diverse field of analysis.This paper describes scikit-image, a collection of image processing algorithms implemented in the Python programming language by an active community of volunteers and available under the liberal BSD Open Source license. The rising popularity of Python as a scientific programming language, together with the increasing availability of a large eco-system of complementary tools, makes it an ideal environment in which to produce an image processing toolkit.The project aims are:1.To provide high quality, well-documented and easy-to-use implementations of common image processing algorithms.Such algorithms are essential building blocks in many areas of scientific research, algorithmic comparisons and data exploration. In the context of reproducible science, it is important to be able to inspect any source code used for algorithmic flaws or mistakes. Additionally, scientific research often requires custom modification of standard algorithms, further emphasizing the importance of open source.2.To facilitate education in image processing.novice module is provided, not only for teaching programming in the “turtle graphics” paradigm, but also to familiarize users with image concepts such as color and dimensionality. Furthermore, the project takes part in the yearly Google Summer of Code program1https://developers.google.com/open-source/soc (accessed 30 March 2014)., where students learn about image processing and software engineering through contributing to the project.The library allows students in image processing to learn algorithms in a hands-on fashion by adjusting parameters and modifying code. In addition, a 3.To address industry challenges.High quality reference implementations of trusted algorithms provide industry with a reliable way of attacking problems without having to expend significant energy in re-implementing algorithms already available in commercial packages. Companies may use the library entirely free of charge, and have the option of contributing changes back, should they so wish.One of the main goals of scikit-image is to make it easy for any user to get started quickly—especially users already familiar with Python’s scientific tools. To that end, the basic image is just a standard NumPy array, which exposes pixel data directly to the user. A new user can simply load an image from disk (or use one of scikit-image’s sample images), process that image with one or more image filters, and quickly display the results:from skimage import data, io, filterimage = data.coins  # or any NumPy array!edges = filter.sobel(image)io.imshow(edges)data.coins, an example image shipped with scikit-image. For a more complete example, we import NumPy for array manipulation and matplotlib for plotting )ax0, ax1, ax2, ax3, ax4, ax5  = axes.flatax0.imshowax0.set_titleax0.axis('off')Since the image is represented by a NumPy array, we can easily perform operations such as building a histogram of the intensity values.# Histogram.values, bins = np.histogram)ax1.plotax1.set_xlim(xmax=256)ax1.set_yticksax1.set_aspect(.2)ax1.set_titlefilter.threshold_adaptive where the threshold value is the weighted mean for the local neighborhood of a pixel.To divide the foreground and background, we threshold the image to produce a binary image. Several threshold algorithms are available. Here, we employ # Apply threshold.from skimage.filter import threshold_adaptivebw = threshold_adaptiveax2.imshowax2.set_titleax2.axis('off')feature.peak_local_max can be used to return the coordinates of local maxima in an image.We can easily detect interesting features, such as local maxima and edges. The function # Find maxima.from skimage.feature import peak_local_maxcoordinates = peak_local_maxax3.imshowax3.autoscaleax3.plotax3.set_titleax3.axis('off')filter.canny)   detects # Detect edges.from skimage import filteredges = filter.cannyax4.imshowax4.set_titleax4.axis('off')morphology.label) that can be used to extract a sub-picture. Finally, physical information such as the position, area, eccentricity, perimeter, and moments can be extracted using measure.regionprops.Then, we attribute to each coin a label (# Label image regions.from skimage.measure import regionpropsimport matplotlib.patches as mpatchesfrom skimage.morphology import labellabel_image = label(edges)ax5.imshowax5.set_titleax5.axis('off')for region in regionprops(label_image):    # Draw rectangle around segmented coins.    minr, minc, maxr, maxc = region.bbox    rect = mpatches.Rectangle,                              maxc - minc,                              maxr - minr,                              fill=False,                              edgecolor='red',                              linewidth=2)    ax5.add_patch(rect)plt.tight_layoutplt.showscikit-image thus makes it possible to perform sophisticated image processing tasks with only a few function calls.2https://www.ohloh.net/p/scikit-image The package can be installed on all major platforms  from, amongst other sources, the Python Package Index (PyPI),3http://pypi.python.org Continuum Analytics Anaconda,4https://store.continuum.io/cshop/anaconda Enthought Canopy,5https://www.enthought.com/products/canopy Python,6https://code.google.com/p/pythonxy NeuroDebian .The scikit-image project started in August of 2009 and has received contributions from more than 100 individuals.roDebian  and GNU/As of version 0.10, the package contains the following sub-modules:•color: Color space conversion.•data: Test images and example data.•draw: Drawing primitives  that operate on NumPy arrays.•exposure: Image intensity adjustment, e.g., histogram equalization, etc.•feature: Feature detection and extraction, e.g., texture analysis, corners, etc.•filter: Sharpening, edge finding, rank filters, thresholding, etc.•graph: Graph-theoretic operations, e.g., shortest paths.•9http://pillow.readthedocs.org/en/latest/ (accessed 30 May 2015). and FreeImage.10http://freeimage.sourceforge.net/ (accessed 15 May 2015).io: Wraps various libraries for reading, saving, and displaying images and video, such as Pillow•measure: Measurement of image properties, e.g., similarity and contours.•morphology: Morphological operations, e.g., opening or skeletonization.•novice: Simplified interface for teaching purposes.•restoration: Restoration algorithms, e.g., deconvolution algorithms, denoising, etc.•segmentation: Partitioning an image into multiple regions.•transform: Geometric and other transforms, e.g., rotation or the Radon transform.•viewer: A simple graphical user interface for visualizing results and exploring parameters.11http://scikit-image.org/docs/dev/api/api.htmlFor further details on each module, we refer readers to the API documentation online.M, N, 3) for an RGB color image with M vertical and N horizontal pixels; and a numeric data type, such as float for continuous-valued pixels and uint8 for 8-bit pixels. Our use of NumPy arrays as the fundamental data structure maximizes compatibility with the rest of the scientific Python ecosystem. Data can be passed as-is to other tools such as NumPy, SciPy, matplotlib, scikit-learn  or −1 and 1 (signed images), while 8-bit images are expected to have values in {0, 1, 2, …, 255}. We provide utility functions, such as The purpose of scikit-image is to provide a high-quality library of powerful, diverse image processing tools free of charge and restrictions. These principles are the foundation for the development practices in the scikit-image community.Modified BSD license, which allows unrestricted redistribution for any purpose as long as copyright notices and disclaimers of warranty are maintained . This enables the core developers and other interested parties to comment on specific lines of proposed code changes, and for the proponents of the changes to update their submission accordingly. Once all the changes have been approved, they can be merged automatically. This process applies not just to outside contributions, but also to the core developers.We ensure high code quality by a thorough review process using the pull request interface on GitHub.15https://travis-ci.org, https://coveralls.io (accessed 30 March 2014). automatically checks each commit for unit test coverage and failures on both Python 2 and Python 3. Additionally, the code is analyzed by flake8 .. In this section we illustrate two real-world usage examples of scikit-image in scientific research.The package includes a number of algorithms with broad applications across image processing research, from computer vision to medical image analysis. We refer the reader to the current API documentation for a full listing of current capabilitiestransform.hough_circle) providing the drop radius and its center. Then, a smaller concentric circle is drawn (draw.circle_perimeter) and used as a mask to extract intensity values from the image. Repeating the process on each image in the stack, collected pixels can be assembled to make a space–time diagram. As a result, a complex stack of images is reduced to a single image summarizing the underlying dynamic process.First, we consider the analysis of a large stack of images, each representing drying droplets containing nanoparticles see . As the Next, in regenerative medicine research, scikit-image is used to monitor the regeneration of spinal cord cells in zebrafish embryos . This prmeasure.profile_line function measures the fluorescence along the cord, directly proportional to the number of cells. We can thus monitor the recovery process and determine which treatments prevent or accelerate recovery.To understand how spinal cords regenerate in these animals, injured cords are subjected to different treatments. Neuronal precursor cells  makes it ideal for educational use, either via self-taught exploration or formal training sessions.The online gallery of examples not only provides an overview of the functionality available in the package but also introduces many of the algorithms commonly used in image processing. This visual index also helps beginners overcome a common entry barrier: locating the class  and name of operation desired, without being proficient with image processing jargon. For many functions, the documentation includes links to research papers or Wikipedia pages to further guide the user.Demonstrating the broad utility of scikit-image in education, thirteen-year-old Rishab Gargeya of the Harker School won the Synopsys Silicon Valley Science and Technology Championship using scikit-image in his project, “A software based approach for automated pathology diagnosis of diabetic retinopathy in the human retina” .filter.rank.median) and a Gaussian filter (filter.gaussian_filter), demonstrating that a median filter preserves straight lines much better.We have delivered image processing tutorials using scikit-image at various annual scientific Python conferences, such as PyData 2012, SciPy India 2012, and EuroSciPy 2013. Course materials for some of these sessions are found in Finally, easy access to readable source code gives users an opportunity to learn how algorithms are implemented and gives further insight into some of the intricacies of a fast Python implementation, such as indexing tricks and look-up tables.Due to the breadth and maturity of its code base, as well as the its commercial-friendly license, scikit-image is well suited for industrial applications.http://www.btimaging.com) designs and builds tools that use photoluminescence (PL) imaging for photovoltaic applications. PL imaging can characterize the quality of multicrystalline silicon wafers by illuminating defects that are not visible under standard viewing conditions. transform.hough_line) finds the wafer edges in order to segment the wafer from the background. scikit-image is also used for feature extraction. Crystal defects (dislocations) are detected using a band-pass filter, which is implemented as a Difference of Gaussians (filter.gaussian_filter).BT Imaging . scikit-image performs file I/O (io.imread), histogram equalization , and aligns a visible wavelength image with a thermal image (transform.AffineTransform). The system determines the surface temperature of a subject’s skin and detects situations where the face is being obscured.scikit-image is also applied in a commercial setting for biometric security applications. AICBT Ltd uses multispectral imaging to detect when a person attempts to conceal their identity using a facial mask.https://github.com/scikit-image/scikit-image-demos.This section gives a step-by-step outline of how to perform panorama stitching using the primitives found in scikit-image. The full source code is at The “ImageCollection” class provides an easy way of representing multiple images on disk. For efficiency, images are not read until accessed.from skimage import ioic = io.ImageCollection('data/*')from skimage.color import rgb2grayfrom skimage import transformimage0 = rgb2grayimage1 = rgb2grayimage0 = transform.rescaleimage1 = transform.rescale“Oriented FAST and rotated BRIEF” (ORB) features  are detefrom skimage.feature import ORB, match_descriptorsorb = ORBorb.detect_and_extract(image0)keypoints1 = orb.keypointsdescriptors1 = orb.descriptorsorb.detect_and_extract(image1)keypoints2 = orb.keypointsdescriptors2 = orb.descriptorsmatches12 = match_descriptorsTo filter the matches, we apply RANdom SAmple Consensus (RANSAC) , a commofrom skimage.measure import ransac# Select keypoints from the source (image to be# registered) and target (reference image).src = keypoints2]dst = keypoints1]model_robust, inliers = \    ransac, ProjectiveTransform,           min_samples=4, residual_threshold=2)Next, we produce the panorama itself. The first step is to find the shape of the output image by considering the extents of all warped images.r, c = image1.shape[:2]# Note that transformations take coordinates in#  format, not , in order to be# consistent with most literature.corners = np.array# Warp the image corners to their new positions.warped_corners = model_robust(corners)# Find the extents of both the reference image and# the warped target image.all_corners = np.vstack)corner_min = np.mincorner_max = np.maxoutput_shape = (corner_max - corner_min)output_shape = np.ceil(output_shape[::-1])The images are now warped according to the estimated transformation model. Values outside the input images are set to −1 to distinguish the “background”.warp takes the inverse mapping as input.A shift is added to ensure that both images are visible in their entirety. Note that from skimage.color import gray2rgbfrom skimage.exposure import rescale_intensityfrom skimage.transform import warpfrom skimage.transform import SimilarityTransformoffset = SimilarityTransform(translation=-corner_min)image0_ = warpimage1_ = warp.inverse,               output_shape=output_shape, cval=-1)An alpha channel is added to the warped images before merging them into a single image:def add_alpha:    """Add an alpha layer to the image.    The alpha layer is set to 1 for foreground    and 0 for background.    """    rgb = gray2rgb(image)    alpha = (image != background)    return np.dstack)image0_alpha = add_alpha(image0_)image1_alpha = add_alpha(image1_)merged = alpha = merged# The summed alpha layers give us an indication of# how many images were combined to make up each# pixel.  Divide by the number of images to get# an average.merged /= np.maximumThe merged image is shown in To blend images smoothly we make use of the open source package Enblend , which iIn this section, we describe other libraries with similar goals to ours.Mahotas contains many similar functions, and is furthermore also designed to work with NumPy arrays . Finally, the closed source nature of the toolbox prevents users from learning from the code or modifying it for specific purposes, which is a common necessity in scientific research. We refer readers back to the Development Practices section for a summary of the practical and philosophical advantages of our open-source licensing.In many respects, the OpenCV is a BSD-licensed open-source library focused on computer vision, with a separate module for image processing  support.We also invite readers to submit their own feature requests to the mailing list for further discussion.19https://www.ohloh.net/p/scikit-image (accessed 15 May 2014). and the team is excited to collaborate with others to see it grow even further, and to establish it the de facto library for image processing in Python.scikit-image provides easy access to a powerful array of image processing functionality. Over the past few years, it has seen significant growth in both adoption and contribution,


Nocardia sp. strain BMG111209 is a non-Frankia actinobacterium isolated from root nodules of Casuarina glauca in Tunisia. Here, we report the 9.1-Mbp draft genome sequence of Nocardia sp. strain BMG111209 with a G + C content of 69.19% and 8,122 candidate protein-encoding genes. Frankia, which results in the formation of root nodule structures  using a hybrid of Illumina (http://www.jgi.doe.gov). The Illumina and PacBio sequence data were assembled using Allpaths–LG (version r42328) (The draft genome of Illumina  and Paci r42328) . The finNocardia BMG111209 genome was annotated using the JGI annotation pipeline  biosynthesis pathways and the presence of a hup operon encoding an Ni-hydrogenase suggesting possible roles in their functioning as a plant-endophyte.The assembled pipeline , 18 and pipeline . The draARMU00000000. The version described in this paper is the first version, ARMU01000000.This whole-genome shotgun sequence has been deposited at DDBJ/EMBL/GenBank under the accession number