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      Application of the omics sciences to the study of Naegleria fowleri, Acanthamoeba spp., and Balamuthia mandrillaris: current status and future projections Translated title: Application des sciences de l’omique à l’étude de Naegleria fowleri, Acanthamoeba spp. et Balamuthia mandrillaris : état actuel et projections futures

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          Abstract

          In this review, we focus on the sequenced genomes of the pathogens Naegleria fowleri, Acanthamoeba spp. and Balamuthia mandrillaris, and the remarkable discoveries regarding the pathogenicity and genetic information of these organisms, using techniques related to the various omics branches like genomics, transcriptomics, and proteomics. Currently, novel data produced through comparative genomics analyses and both differential gene and protein expression in these free-living amoebas have allowed for breakthroughs to identify genes unique to N. fowleri, genes with active transcriptional activity, and their differential expression in conditions of modified virulence. Furthermore, orthologous genes of the various nuclear genomes within the Naegleria and Acanthamoeba genera have been clustered. The proteome of B. mandrillaris has been reconstructed through transcriptome data, and its mitochondrial genome structure has been thoroughly described with a unique characteristic that has come to light: a type I intron with the capacity of interrupting genes through its self-splicing ribozymes activity. With the integration of data derived from the diverse omic sciences, there is a potential approximation that reflects the molecular complexity required for the identification of virulence factors, as well as crucial information regarding the comprehension of the molecular mechanisms with which these interact. Altogether, these breakthroughs could contribute to radical advances in both the fields of therapy design and medical diagnosis in the foreseeable future.

          Translated abstract

          Dans cette revue, l’accent est mis sur les génomes séquencés des agents pathogènes Naegleria fowleri, Acanthamoeba spp. et Balamuthia mandrillaris, et les découvertes remarquables concernant la pathogénicité et l’information génétique de ces organismes, en utilisant des techniques liées aux diverses branches de l’omique comme la génomique, la transcriptomique et la protéomique. Actuellement, de nouvelles données produites par des analyses génomiques comparatives et l’expression différentielle des gènes et des protéines dans ces amibes libres ont permis des percées pour identifier des gènes uniques à N. fowleri, des gènes avec une activité transcriptionnelle active et leur expression différentielle dans des conditions de virulence modifiée. En outre, les gènes orthologues des divers génomes nucléaires des genres Naegleria et Acanthamoeba ont été regroupés. Le protéome de B. mandrillaris a été reconstruit grâce aux données du transcriptome, et la structure de son génome mitochondrial décrite de manière détaillée, mettant ainsi une caractéristique unique à jour : un intron de type I avec la capacité d’interrompre les gènes par son activité d’auto-épissage des ribozymes. Avec l’intégration des données issues des diverses sciences omiques, il existe une approximation potentielle qui reflète la complexité moléculaire requise pour l’identification des facteurs de virulence, ainsi que des informations cruciales concernant la compréhension des mécanismes moléculaires avec lesquels ceux-ci interagissent. Dans l’ensemble, ces percées pourraient contribuer à des progrès notables à la fois dans les domaines de la conception de la thérapie et du diagnostic médical dans un avenir proche.

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          Comparative genome and phenotypic analysis of three Clostridioides difficile strains isolated from a single patient provide insight into multiple infection of C. difficile

          Background Clostridioides difficile is a Gram-positive, obligate anaerobic spore-forming bacterium, which can act as nosocomial human pathogen colonizing the intestinal tract and causing disease [1]. Symptoms of C. difficile infection (CDI) can range from mild diarrhea to pseudomembranous colitis or life-threatening toxic megacolon [2, 3]. C. difficile has been described by Miller et al. in 2011 [4] together with methicillin-resistant Staphylococcus aureus (MRSA) as the most common cause of nosocomial infections in the United States. Consequently, C. difficile was prioritized in the highest rank for surveillance and epidemiological research [5]. Strains of C. difficile are currently distinguished by PCR ribotyping (comparison of pattern of PCR products of the 16S–23S rRNA intergenic spacer region), which allows to follow epidemic infection routes [6]. Ribotype (RT) 027 was responsible for dynamic increase of CDIs in North-America and Europe, which quadrupled the number of CDI victims between 2004 and 2007 [7]. However, this epidemic outbreak had been successfully controlled with a decrease in CDI infection in 2008 [8, 9]. The infection line and the spread of the outbreak in Germany has been traced by a genome sequence-based BEAST-analysis [10]. Thus, the mutation rate of the strains challenged by the immune system of the patients was sufficient to track the transmission of the pathogen C. difficile from patient to patient. The dynamic adaptation of pathogens challenged by a host immune defense is the reason why host/pathogen systems have been used as model-system to investigate the speed of genome evolution [11, 12]. Genome analysis of representative strains of C. difficile from the PCR ribotypes 001, 017, 027 and 078 revealed the presence of distinct genomes [7]. The investigated genomes contain an extensive pan-genome shaped by horizontal gene transfer (HGT). The quantification of HGT events revealed that 11% of the whole genome is consisting of mobile elements [7, 13–15]. The described genome diversity of the species contrasts with the phenotypic similarity of isolated strains with respect to growth, virulence and pathogenicity [14]. Notably, the genes encoding the toxins TcdA and TcdB assigned to the CDI virulence [16, 17] are located on the pathogenicity locus (PaLoc) which constitutes a genomic island. This indicates that HGT is involved in the evolution of toxigenic C. difficile strains [18]. In E. coli, HGT events between different strains have been identified as an important source for new combination of virulence factors and thus for the emergence of novel pathotypes [19]. In CDI cases, multiple infections by C. difficile strains, which are different in morphology and virulence, have been observed [20, 21], thereby indicating the opportunity to exchange genetic material through HGT events between the strains involved. In this study, we present a comparative phenotypic and genome analysis of three morphologically different C. difficile strains isolated from a single patient. Two of the strains belong to RT 027 (DSM 27638 and DSM 27640) and one to RT 012 (DSM 27639). Methods Isolation of strains A stool sample from a patient with diarrhea was cultivated anaerobically on Clostridium difficile (CLO) agar plates (bioMérieux, Nürtingen, Germany), which is a selective medium for C. difficile. After 48 h of cultivation at 37 °C, colonies characteristic for C. difficile were visible and were confirmed by MALDI-TOF mass spectrometry (Biotyper, Bruker Daltonics, Bremen, Germany) with score values of ≥2000. Isolated strains were deposited at the DSMZ under the accession numbers DSM 27638, DSM 27639 and DSM 27640. Phenotypic characterization General growth conditions C. difficile strains were grown at 37 °C in an anaerobic chamber (Coy Laboratory Products, Michigan USA) under an atmosphere of 5% CO2, 5% H2, 90% N2 or in a jar (Merck, Darmstadt, Germany) using an anaerobic gas pack (bioMérieux, Nürtingen, Germany). For liquid cultures, BHIS (brain heart infusion; BD, Heidelberg, Germany) supplemented with 0.5% yeast extract (BD, Heidelberg, Germany) and 0.03% L-cysteine (Sigma, Taufkirchen, Germany) was used. Cultivation on plates was performed using chromID™ C. difficile agar (CDIFF), Clostridium difficile agar (CLO) or Columbia agar with 5% sheep blood (COS) (bioMérieux Nürtingen, Germany). Plates were incubated for 24 to 48 h. Sporulation assay Sporulation rates were determined according to Burns et al., [22]. Briefly, an overnight culture of the respective strain was diluted 1:100 with fresh BHIS and was grown until an optical density (OD600) of 0.2 to 0.4. This culture was again diluted 1:100 with fresh BHIS and cultivated for five days. An aliquot of the culture was heated for 25 min at 60 °C to kill the vegetative cells. Dilution series of an untreated and the heated sample with sterile saline was performed and spotted on CDIFF plates. Colony forming units (CFU) were analyzed after 24 h of incubation. Co-cultivation of C. difficile strains An overnight culture was adjusted to an OD600 of 0.1 in fresh BHIS. 400 μl of the cells were incubated in one well of a 24-well plate (Greiner Bio-One, Frickenhausen, Germany). A ThinCert™ insert (pore size 0.4 μm) was placed in this well and 400 μl of the respective C. difficile strain was added. The insert allows the diffusion of metabolites between the two cultures but not of cells or spores. A dilution series of the cells at the time point zero was spotted on CDIFF plates to ensure that equal amounts of the respective strains were used for co-cultivation. After 24 h of incubation, the cells in the wells and inserts were resuspended thoroughly and adjusted to equal volumes. A dilution series of the cells was performed on CDIFF agar plates and incubated for 24 h. To assess whether the insert membrane is tight for C. difficile, controls were performed with (i) bacteria in the insert and sterile medium in the well and (ii) sterile medium in the insert and bacteria in the well. After plating aliquots on CDIFF plates, no colonies were formed after a 24 h incubation time for the medium controls, indicating that bacteria do not pass the insert membrane in relevant numbers within the 24 h incubation time. Mobility assay The motility of C. difficile strains was tested by stab-inoculation of a fresh single colony grown on BHI-agar in 0.175–0.3% semi-solid BHI-agar. Anaerobic incubation at 37 °C, and monitoring of the developed diffusion radius around the inoculation stab for the following days, were performed. 0.3% BHI-agar plates were prepared and anaerobically incubated for 3 h before inoculation. Plates were inoculated in the center of the plate with a single fresh C. difficile colony and incubated under anoxic condition (5% H2, 5% CO2, 90% N2) at 37 °C. 1 and 2 d post inoculation, plates were removed from the anaerobic atmosphere for scanning of the plates. Motility assay on agar plates was performed incubating plates upside down and with the lid upturned to avoid problems with condensing water. Hungate tubes containing semi-solid 0.175% BHI-agar were incubated anaerobically overnight before inoculation. Agar was inoculated in the center of the hungate tube with a single fresh C. difficile colony using an inoculation needle in four replicates and incubated anaerobically (5% H2, 95% N2) at 37 °C. Diffusion radius around the inoculation stab was monitored taking pictures 1, 2 and 3 d post inoculation. Transmission electron microscopy For visualization of C. difficile cells via Transmission Electron Microscopy (TEM) cells were negatively stained using 1% (w/v) uranyl acetate. C. difficile cultures were inoculated and grown to exponential or stationary phase. Cultures were either used directly for sample preparation, or were previously washed to get rid of media ingredients. Therefore 2 ml liquid culture were centrifuged at 4000 rpm for 5 min, washed with 1 ml 50 mM Tris and centrifuged again. Subsequently, the pellet was resolved in 200 μl Tris. For sample preparation, an EM S160–3 cupper grid was incubated on a droplet of liquid C. difficile culture, or washed cells, for 1 min to allow absorption of cells to the grid’s carbon film. The grid was carefully semi-dried with a filter, preventing crystallization of media ingredients on the carbon film. The grid was washed in a droplet of deionized H2O, filter-dried and negatively stained on a droplet of 1% (w/v) uranyl acetate solution for 15 s. Afterwards the grid was completely dried with a filter and analyzed using a Jeol JEM-1011 TEM. Antibiotic resistance susceptibility tests Susceptibility to metronidazole, erythromycin, vancomycin, rifampicin and moxifloxacin was performed using Etest® strips (bioMérieux, Nürtingen, Germany). Grown cells (according the described general growth conditions above) were adjusted with 0.9% saline to a McFarland standard 1 and swabbed onto Mueller-Hinton agar supplemented with 5% horse blood and 20 mg/l β-NAD+ (bioMérieux, Nürtingen, Germany). Plates were incubated anaerobically at 37 °C and MIC breakpoints were read after 48 h. Control strains (Table 1) were included to verify the reproducibility of the test. Table 1 Antibiotic resistance patterns of the three C. difficile strains Isolate Rifampicin bVancomycin bMetronidazole cMoxifloxacin Erythromycin DSM 27638 a0.004 S (0.5) S (0.38) R (>32) R (>256) DSM 27639 S (0.003) S (0.75) S (0.25) S (2) R (>256) DSM 27640 a0.004 S (0.38) S (0.25) R (>32) R (>256) DSM 27543 S (0.003) S (0.5) S (0.25) S (2) R (>256) DSM 27147 a0.004 S (0.5) S (0.38) R (>32) R (>256) May be tested for epidemiological purposes only (ECOFF 4 mg/L (EUCAST Clinical Breakpoint Table v. 7.1.). DSM 27543 (630) and DSM 27147 (R20291) served as controls MIC given in mg/mL, S sensitive, R resistant aNot used clinically. May be tested for epidemiological purposes only (ECOFF 0.004 mg/L). Vancomycin: R > 2 mg/L. Metronidazole: R > 2 bThe breakpoints are based on epidemiological cut-off values, which distinguish wild-type isolates from those with reduced susceptibility cNot used clinically DNA extraction, genome sequencing, de novo genome assembly and genome annotation For genome sequencing the strains were cultivated anaerobically in Wilkins-Chalgren Anaerobe Broth (Oxoid, Basingstore, United Kingdom) at 37 °C. Genomic DNA was extracted as described previously [23, 24]. Genome sequencing of the C. difficile strains was carried out on the PacBio RSII (Pacific Biosciences, Menlo Park, CA) using P5 chemistry. Genome assembly was performed with the RS_HGAP_Assembly.3 protocol included in SMRT Portal version 2.3.0. The chromosomal contigs generated were trimmed, circularized, and adjusted to dnaA as the first gene. In parallel, genome sequencing of the C. difficile strains was carried out on a Genome Analyzer GAIIx (Illumina, San Francisco, CA) in a 112 bp paired-end single-indexed run Quality improvement of the final consensus sequence was performed with the Burrows-Wheeler Aligner (BWA) using bwa aln and bwa sampe [25] mapping the Illumina reads onto the obtained chromosomal contigs from the PacBio sequencing. A final quality score of QV60 was attained. Automated genome annotation was carried out using Prokka [26]. Subsequentially, selenocysteine proteins were annotated manually. Complete genome sequences have been submitted to GenBank under the accession numbers CP011846.1 (DSM 27638), CP011847.1 (DSM 27639) and CP011848.1 (DSM 27640). No extrachromosomal genetic elements were observed within this sequencing study. Comparative genomics The genomes of strains DSM 27638, DSM 27639 and DSM 27640 were compared with finished closed references genomes selected as members of the corresponding RTs, Comparative genomics included three strains belonging to the most virulent RT 027 (non-epidemic strain CD196, the epidemic and highly virulent strain R20291 [14], and the bovine isolate 2,007,855), three other strains belong to recently emerging RTs 017 (CF5 and M68) and RT 078 (M120). The RT 012 is represented by strain 630 [23, 27]. All analyzed strains are listed in Table 2. Orthologous proteins were determined with ProteinOrtho [28] applying default parameters. Circular visualizations and comparisons of shared nucleotide regions of the genomes have been produced with BRIG [29] and linear visualizations with MAUVE [30]. Identification of genomic islands has been done with Island viewer 3 [31]. All identified regions have been manually curated using UniProtKB/Swiss-Prot and TrEMBL database (www.uniprot.org). In detail, comparison of related genome regions have been done with ACT and Artemis [32]. Phylogenomics based on whole genome alignments has been performed by using Phylomark [33]. Synteny analysis and SNP prediction have been performed with nucmer from the mummer program suite [34]. Table 2 Genome sequences used in this study Strain Ribotype Toxino-type Genome size Isolation (year/country) Accession number Reference DSM 27638a 027 III 4,229,698 2015/Germany CP011846.1 This study DSM 27639a 012 0 4,263,997 2015/Germany CP011847.1 This study DSM 27640a 027 III 4,229,629 2015/Germany CP011848.1 This study 630a 012 0 4,274,782 1982/Switzerland CP010905.2 [27] CF5b 017 VIII 4,159,517 1995/Belgium FN665652.1 [14] M68b 017 VIII 4,308,325 2006/Ireland NC_017175.1 [14] CD196c 027 III 4,110,554 1985/France NC_013315.1 [49] R20291d 027 III 4,191,339 2006/UK FN545816.1 [14] 2007855d 027 III 4,179,867 2007/US FN665654.1 [14] M120b 078 V 4,047,729 2007/UK NC_017174.1 [51] aPacBio/Illumina hybrid assembly b454/Illumina hybrid assembly c454/Sanger sequencing d454 sequencing Results and discussion Phenotypic characterization Three C. difficile strains (DSM 27638, DSM 27639 and DSM 27640) exhibiting different phenotypes on solid medium have been isolated from one stool sample of a single patient suffering from CDI. The isolate DSM 27639 formed colony types that were white and smooth with clearly defined edges (Fig. 1). The other two isolates DSM 27638 and DSM 27640 had a rougher surface and seemed to spread on the agar plate (Fig. 1). Both isolates mainly differed in color; isolate DSM 27638 was grayish compared to isolate DSM 27640 which appeared rather gray beige. This initial observation indicated that the patient was infected with more than only one C. difficile strain. Since it has been reported that multiple infection with pathogens like C. difficile occur [20, 21], we aimed to more precisely characterize the respective phenotypic and genotypic differences that occurred during this multiple infection. Fig. 1 Colony morphology of C. difficile strains. Strains were grown anaerobically (5% H2, 95% N2) on commercial Clostridium difficile agar (CLO) for 2 days at 37 °C. DSM 27638 (a) and DSM 27640 (c) show irregular colony shape with shiny surfaces and white color. Colonies from DSM 27640 (c) are more opaque than colonies from DSM 27638 (a). Colony shape of DSM 27639 (b) looks nearly filamentous, colony surface is smooth and the color is cloudy and whitish Toxinotyping has been used for distinguishing C. difficile strains. In this regard, toxin A and B genes located on the PaLoc are considered to be the major virulence factors of C. difficile. Sequencing of the complete genomes showed that the PaLocs from all three isolates were intact. As expected, the toxin loci of DSM 27638 and DSM 27640 grouped to toxinotype III, which is observed for strains belonging to RT 027 [35]. The toxin locus of isolate DSM 27639 belonged to toxinotype 0, which correlated with strains grouping into RT 012 [35]. Both RT 027 isolates DSM 27638 and DSM 27640 exhibited the typical antimicrobial susceptibility pattern of this RT, including high resistance against erythromycin and moxifloxacin (Table 1). In contrast, the RT 012 isolate DSM 27639 was susceptible to moxifloxacin. All isolates were susceptible to vancomycin and metronidazole that are antibiotics commonly used in CDI therapy [36]. It has been reported that multiple C. difficile strains can co-exist in an in-vitro human gut model although exhibiting different growth rates [37], we investigated the growth behavior of the three isolates under pure culture conditions as well as under co-cultivation conditions. However, the strains showed an identical growth behavior in BHIS under standard conditions (Additional file 1: Figure S1) In addition, all strains had the same maximal sporulation ability shown by comparable amounts of germinated spores on plates after incubation under harsh nutrient starvation (Additional file 2: Figure S2). Co-cultivation of the isolates showed that none of them had either a negative or a positive effect on the growth of any of the other isolates or the growth of reference strain 630 (data not shown). The absence of intra-species competition most likely has supported their co-existence in the patient. However, those in vitro results obviously cannot reflect the complex situation in the human host where nutrients are limiting and the different isolates are challenged by the host immune system and complex gut microbial community. The clinical isolates DSM 27638, DSM 27639 and DSM 27640 exhibit representative phenotypic features of the toxinotype they belong to which is confirmed by the phylogenetic clustering based on whole genome sequence comparison (Fig. 2). However, phenotypic analysis could not explain the presence of two RTs in one patient. Fig. 2 Whole genome alignment based phylogenomic tree. Strain DSM 27639 clusters with reference strain 630 and strains DSM 27638/40 with all RT 027 strains. The tree has been calculated using Phylomark with default parameters. The clinical isolates are marked in red, due to the extreme low editing distance the node of DSM 27638 and DSM 27640 has been collapsed General genome comparison To determine the genomic features correlating with the observed colony phenotypes we performed complete genome sequencing of all three isolates. Their genomes were compared with seven publicly available closed C. difficile genomes including reference genomes of four different PCR ribotypes. A whole genome alignment using Phylomark [33] was used to assign strains DSM 27638 and DSM 27640 to RT 027 and the isolate DSM 27639 to RT 012 (Fig. 2). The genome alignment of these isolates and reference strains using MAUVE showed that all C. difficile strains share a complete syntenic chromosome interrupted by mobile elements, as it has been observed in other virulent clostridia [38] (Additional file 3: Figure S3). To determine the core genome orthologous coding sequences (CDS) between all C. difficile strains were identified. Thus, we identified a core genome of 2669 CDS shared by all strains (Fig. 3). Consistent with the antibiotic dependent pathogenicity of CDI the core genomes comprises a number of genes assigned to antimicrobial resistances (Additional file 4: Table S1), including the beta-lactamase-inducing penicillin-binding protein BlaR; the quaternary ammonium compound-resistance protein SugE, and the vancomycin/teicoplanin-resistance proteins VanG, VanV and VanW. Resistance of C. difficile against the fluoroquinolone moxifloxacin is characteristic for most RT 027 strains and provides them with a selective advantage in comparison to other ribotypes when this antibiotic is used. The historical RT 027 strain CD196 in contrast to recently isolated RT 027 strains is moxifloxacin susceptible [39]. It was already shown that a single point mutation in the DNA gyrase subunit A-encoding gene gyrA of C. difficile leads to fluoroquinolone resistance [40]. In contrast to C. difficile reference strain 630 and isolate DSM 27639, the RT 027 strain 2,007,855 and the isolates DSM 27638 and DSM 27640 are resistant to fluoroquinolones. Sequence analysis of the GyrA protein confirmed that all moxifloxacin-resistant C. difficile strains contain a single transition mutation resulting in the amino acid substitution Thr-82-Ile (Additional file 5: Figure S4) [41]. Fig. 3 Core/Pan-genome calculation of the RT 012, RT 017, RT 027, and RT 078. The four ribotypes share a core genome of 2669 genes. The genomes used to generate the protein datasets are indicated. Orthologous proteins have been identified with ProteinOrtho software (Lechner et al., [28]) In addition, strain-specific and ribotype-specific CDS were identified. The locations of regions of genetic difference between the strains are highlighted in the concentric circular chromosome representations of the analyzed ten genomes (Fig. 4). Strain specific genes are often found to be encoded in regions that have been identified as prophages or conjugative transposons (Table 3). Fig. 4 Circular representations of C. difficile chromosomes generated with BRIG software. From the outside: circle 1 shows identified mobile elements (black – prophages P1–7, pink – conjugative transposons CT). Circle 2 shows reference genome a strain DSM 27638 / DSM 27640, b strain DSM 27639). The most inner circle represents scale (in kb), second inner – GC skew for reference genome, third – GC content graph. Inner rings represent analyzed genome sequences of red colors ribotype 027 (the most dark red: DSM 27638 then 2,007,855, R20291, and light red 196); blue colors represent 012 ribotype (dark blue: 630, light blue: DSM 27639); green colors represent ribotype 017 (dark green: CF5, light green: M68) and yellow color represent strain M120 belonging to RT 078 Table 3 Mobile elements of strains DSM 27638 and DSM 27639a Start Stop Length [bp] ORFs Mobile element and gene content DSM 27638  284,586 301,831 17,244 16 PHAGE (P1) (not found in 012 and 017 ribotypes)  398,255 402,824 4569 7 ABC transporter, two-component system, transposase  501,871 511,046 9229 10 transposase, hydrolases, transcriptional regulator, oligo-1,6-glucosidase, PTS system transporter subunit IIABC  518,083 528,817 10,734 10 lantibiotic resistance, two two-component systems, ABC transporter  662,517 674,897 12,380 11 ABC transporter, two-component system, transcriptional regulator  934,705 938,946 4241 5 lantibiotic resistance two-component system, two-component system  1,438,093 1,465,397 27,304 30 PHAGE (P2)  1,680,933 1,736,907 55,974 69 PHAGE (P3) (ribotype 027 specific)  2,046,513 2,066,289 19,776 6 PHAGE (P4) (ribotype 027 specific)  3,441,029 3,447,002 5973 6 conjugative transposon  3,478,606 3,491,098 12,492 8 integrase, chromosome segregation ATPase  3,489,961 3,527,152 37,191 26 PHAGE (P5) (ribotype 027 specific)  3,769,213 3,775,340 6127 7 conjugative transposon  3,775,480 3,844,734 69,254 54 PHAGE (P6) (DSM 27638 specific)  3,846,878 3,869,593 22,715 22 conjugative transposon  4,100,257 4,105,353 5096 5 ABC transporter, two-component system  4,134,037 4,164,119 30,082 34 conjugative transposon, multidrug resistance protein (ribotype 027 specific) DSM 27639  1,170,734 1,205,103 34,369 33 conjugative transposon, lantibiotic ABC transporter (DSM 27639 specific)  1,461,445 1,488,797 27,352 30 PHAGE (P1)  1,578,539 1,595,263 16,724 17 conjugative transposon (DSM 27639 specific)  1,580,053 1,595,960 15,907 9 PHAGE (P2) (DSM 27639 specific)  2,047,626 2,068,044 20,418 7 PHAGE (P3) (ribotype 012 specific)  2,083,042 2,091,718 8676 9 PHAGE (P4)  2,263,687 2,285,988 22,301 26 conjugative transposon (DSM 27639 specific)  2,267,275 2,285,716 18,441 11 PHAGE (P5) (DSM 27639 specific)  2,536,302 2,550,493 14,191 23 PHAGE (P6) (ribotype 012 specific)  3,282,029 3,362,995 80,966 84 PHAGE (P7) (DSM 27639 specific) aDSM 27,640 is not included because it is identical to DSM 27638 in all elements. All mobile elements have been predicted by IslandViewer 3, PHASTER and have been manually curated The overall similarity strongly underlines that RT 027 strains are closely related. Sequence data show that six genetic regions (two transposons and four prophages P1, P3, P4, and P5) are unique to the RT 027. The biggest difference observed in the genome of DSM 27638 is the presence of a predicted prophage integrated at 3.78 to 3.84 Mbp flanked by conjugative transposons (Fig. 4, Table 3). Interestingly, there is a conjugative transposon present at position 3.84 to 3.87 Mbp shared by the strains DSM 27638 and DSM 27640 as well as strain R20291 but not by the RT 027 reference strain CD196. This indicates that the four strains might share a common history starting at a RT 027 ancestor that did not contain the conjugative transposon. The ancestor of strains DSM 27638, DSM 27640 and R20291 might have acquired the transposon locus, which in the ancestor of strains DSM 27638 and DSM 27640 was the integration locus of a prophage. Sequence comparison of two RT 012 genomes (630 (DSM 27543) and DSM 27639) revealed a high degree of synteny except for those regions that encode mobile elements (Additional file 3: Figure S3). A circular BLAST based comparison of the DSM 27639 genome focused on the RT 012 genomes revealed that the difference between both genomes correlates directly to predicted prophages and conjugative transposons (Fig. 4 b). Two prophages (P3 and P5) and five transposons are shared exclusively by the genomes of the strains DSM 27639 and 630 and might therefore be acquired by an RT 012 ancestor. The remaining two prophages (P1 and P4) are specific for strain DSM 27639. One prophage region is shared by all nine analyzed strains. Comparative genomics revealed that the biggest difference of the strains isolated from the same patient to the reference genomes is the acquisition or loss of prophages and conjugative transposons, which fits to the observations of Hargreaves et al. and Mullany et al. [18, 42]. Thus we conclude that the strain-specific genes are a result of acquisition of mobile elements, which indicates the importance of these elements for the emergence of virulence. In contrast to the prophage regions, all conjugative transposons correlate with GC-content variations compared to the average GC-content (see Fig. 4). This indicates that the acquisition of the transposons are a more recent event and thus the forces of amelioration of newly acquired genome regions (described in [43] and references therein) to the host genome have had less time to operate. In infectio genome dynamics of DSM 27638 and DSM 27640 The genome sequences of the two RT 027 isolates DSM 27638 and DSM 27640 are almost identical (Additional file 6: Figure S5), which suggest a clonal history of them within the patient [14, 44]. The isolates encode the same number of predicted proteins and differ by only 69 bp in size (Table 2, Fig. 5). A whole genome BLAST comparison of the genomes revealed the differences within six genome regions five of them being found within intergenic regions (Table 4). Two loci represent imperfect inverted repeats upstream of operons, a motif which has been found in Salmonella enterica as regulatory element where the inverted repeat regulates the downstream operon upon inversion [45]. Johnson described the regulation as a reversible flip/flop mechanism. Three inverted loci flanked by inverted repeats have been described as well as a difference between the originally published of the C. difficile genome 630Δerm and a high quality re-sequenced version in Dannheim at el. [27] indicating a reversible nature of these genomic elements. However, a comparison of the reverse complement sequence from isolate DSM 27638 with the sequence of DSM 27640 revealed that the regions differ in six base positions between the two strains. In contrast to the 630Δerm strains the locus differs between strains DSM 27638 and DSM 27640 not only in a reversible inversion. The locus is located upstream of the first CDS of the late flagellum genes and has been investigated in detail by Anjuwon Foster et al. [46] who named the regulatory element as flagellum switch. The sequence of strain DSM 27638 is identical to the 154 bp sequence described for RT 027 in contrast to the DSM 27640 version that contains additionally 4 bp. In contrast, the second inverted repeat, which is located upstream of a diguanylate cyclase, exhibits no difference compared to the reverse complement sequence of the corresponding locus of strain DSM 27640. This observation and the possibility that this kind of inverted repeat may be reversibly inverted [45, 47] challenges the hypothesis that the two genome regions really can be considered as different. Furthermore, the operons located adjacent to the inverted repeat encode transporters where a possible contribution to a macroscopic visible strain difference is at least not obvious. The most prominent sequence difference between the two isolates is generated by the insertion of eight instances of an octamer repeat-unit in isolate DSM 27638 at position 594,943 to 595,006. This 64 bp insertion is responsible for almost the complete size difference of 69 bp of the two genomes (Table 2). As a result DSM 27638 contains 21 repeat-units and DSM 27640 13 repeat-units at the corresponding locus. The repetitive region is located within the intergenic region of a locus that encodes several genes assigned to spore surface components. However, although it is possible that a modification of the regulation of spore surface components might result in the observed phenotypic differences a comparative investigation of the sporulation behavior and the viability of the spores revealed no significant differences between the three isolates (Additional file 2: Figure S2). Since the two isolates are - in contrast to the well investigated reference strain 630 - not yet genetically accessibility, a systematic investigation of the multiple repeat region and its putative contribution to the observed differences of growth phenotypes is not possible to date. The remaining genome sequence differences are three single base insertion, two of them located in intergenic regions and only one impacts an encoding signal peptidase. Fig. 5 Sequence differences of C. difficile isolates DSM 27638 and DSM 27640. Three regions out of six are point mutations. The flagellum switch region is described in detail in Fig. 7. The octamer repeat region and an invertable element are presented in detail Table 4 Sequence differences of C. difficile isolates DSM 27638 and DSM 27640 DSM 27638 DSM 27640 Description 321,766 to 321,922 321,766 to 321,918 six base variations within the flagellum switch, an invertible element downstream of a c-di-GMP riboswitch within the 5’UTR of the flgB-gene 594,884 to 595,051 594,880 to 594,983 octamer repeat upstream of glutaminase GlsA, DSM 27638 contains eight additional instances . Gap at 1,411,589 T at 1,411,522 single base deletion within a poly T stretch generates a disfunctional signal peptidase Sip3 gene in DSM 27638 1,793,982 to 1,794,196 1,793,915 to 1,794,129 invertible element upstream of signaling protein (CDIF27640_01720 resp. CDIF27638_01720). The reverse complement of the DSM 27638 sequence is identical to the DSM 27640 sequence T at 2,096,993 . Gap 2,096,925 single T insertion within an poly T stretch, upstream of stage V sporulation protein S SpoVS A at 2,964,477 . Gap 2,964,408 single A insertion within a poly A stretch, upstream of a purine riboswitch regulated permease (CDIF27638_02797 resp. CDIF27640_02796) The fli locus The fli locus encodes the flagellum of C. difficile, which results in motile peritrichous C. difficile cells [48]. A genome analysis of the fli loci of the three isolates and comparisons with RT 027 and RT 012 reference strains as well as with a non-motile RT 078 control strain confirmed that all structural genes necessary to encode a functional flagellum are present in all three isolates, which could be confirmed via TEM (Fig. 6). Note that that all amino acid sequences of the fli-gene products of strains DSM 27638 and DSM 27640 are identical. Since the intergenic regulatory region upstream of the early stage fli genes is one of only three regional sequence differences identified in the complete genome sequences of DSM 27638 and 27,640 we performed additional phenotypic investigations to verify the expression of a functional flagellum (Fig. 7). In contrast to the non-motile RT 078 control strain, both RT 027 isolates as well as the RT 012 isolate DSM 27639 and the respective control isolates R20291 (RT 027) and 630 (DSM 27543, RT 012) exhibited a spreading diffuse growth indicative for active motility (Additional file 7: Figure S6). Thus the impact of the described genome difference on the initially observed growth phenotype (Fig. 1) remains unsolved. However, it has been reported that the flagellum can have an impact on the adherence to intestinal mucosa and might eventually also influence growth on solid surfaces such as agar plates [46, 49, 50]. Thus it is tempting to speculate that the sequence difference within the fli locus contributes to the observed growth phenotype of the three patient isolates. Fig. 6 Flagella in C. difficile strains. a Arrangement of genes in the flagellar locus. b-d Transmission electron microscopy (TEM) of vegetative cells. The rod-shaped cells of all analyzed C. difficile strains appeared peritrichous flagellated indicating that the flagellar locus is functional. b DSM 27638; c DSM 27639; d DSM 27640 Fig. 7 Comparison of upstream region of flgB in strains DSM 27638 and DSM 27640. a Pairwise comparison of the C. difficile DSM 27638 and DSM 27640 region of inversion displayed using the Artemis Comparison Tool (ACT; http://www.sanger.ac.uk/science/tools/artemis-comparison-tool-act). The red and yellow bars indicate regions of similarity with red bars indicating corresponding regions that are oriented similarly and yellow bars indicating regions oriented in opposite directions; b Alignment of region from DSM 27638 (321766–321,922) and DSM 27640 (321766–321,918); c Alignment of complement/reverse version from DSM 27640 with DSM 27638 original sequence Conclusion The analysis of three phenotypic diverse C. difficile isolates that were isolated simultaneously from a stool sample of a diarrheic patient confirmed that multiple and isochronal infections with different RTs occur. The phenotypic and genetic characterization could not give an answer which strain (if that is a case) caused the CDI since all three isolates harbor apparently an intact complete PaLoc encoding the tcdA and tcdB toxin genes and there are no obvious phenotypic advantages showing that one isolate distinctly differs from the others. However, our sequence-based analysis gave insights into genome evolution in micro- and macroscale, as well as in in infectio adaptation. The genome history of the three analyzed isolates has been tracked by a comparative genome analysis. The acquisition/loss of prophage and conjugative transposons is most impressive. The observation that strains of different RTs within single infection have exchanged genetic material in form of mobile genetic elements indicates that genome variation might be as well an effect of a community-based maintenance of a common pan-genome which would be separate genomic adaptations from evolutionary events. Apparently, inversion events of intergenic regions correlate to phenotypic variation. An in-depth analysis of two isolates from RT 027 indicate an in infection strain adaptation. Thus genome modification events which lead to phenotypic diversification and in long-term to the evolution of new strains can be observed in a single infection event. Additional files Additional file 1: Figure S1. Growth curves in BHIS of DSM 27638, DSM 27639 and DSM 27640. The isolates were grown in brain heart infusion medium containing 0.5% (w/v) yeast extract und 0.03% (w/v) L-cysteine. All isolates have the same growth rate under laboratory conditions as shown as the means of three replicates with standard deviation. (DOCX 55 kb) Additional file 2: Figure S2. Sporulation assay of DSM 27638, DSM 27639 and DSM 27640 on ChromID plates after 5 days incubation on BHIS. All three isolates show a comparable count of spores that germinated on the plate. (DOCX 275 kb) Additional file 3: Figure S3. Mauve whole genome alignments of ten linearized C. difficile strains from four different PCR ribotypes. In this alignment process locally collinear blocks (LCBs) were generated. Boxes with identical colors represent LCB, indicating homologous DNA regions shared between the chromosomes without sequence rearrangement. Lines collate aligned segments between genomes. The vertical bars denote the conservation level, and upward and downward orientations relative to the genome line indicates collinear and inverted regions, respectively. The only non syntenic region of the genomes is indicated by the red box. Sequences outside colored blocks do not have homologues in the other genome. (DOCX 419 kb) Additional file 4: Table S1. Genes assigned to resistance. (DOCX 16 kb) Additional file 5: Figure S4. DNA gyrase subunit A alignment. The resistance phenotype is encoded by the amino acid substitution at the position 82 of GyrA. (DOCX 33 kb) Additional file 6: Figure S5. Genome comparison of C. difficile isolates DSM 27638 and DSM 27640. The genome share a complete highly conserved chromosome reflected by the main diagonal. The repeats are depicted by the blue dots evenly distributed within the graph. The comparison has been calculated with Mummer 3 using default parameters. (DOCX 603 kb) Additional file 7: Figure S6. Motility assay of C. difficile isolates. RT 012 strains (630; DSM 27639), RT 027 strains (R20291; DSM 27640; DSM 27638) and non-motile RT 078 (DSM 29747) as a reference were analyzed on 0.3% BHI-agar. Following 1 to 2 days of post inoculation, the diffusion radius was monitored in semi-solid hungate tubes (A) and on semi-solid agar plates (B), respectively. Note, all strains produced gas. (DOCX 11038 kb)
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            Evaluation and comparison of bioinformatic tools for the enrichment analysis of metabolomics data

            Background Bioinformatic tools for the enrichment of ‘omics’ datasets facilitate interpretation and understanding of data. To date few are suitable for metabolomics datasets. The main objective of this work is to give a critical overview, for the first time, of the performance of these tools. To that aim, datasets from metabolomic repositories were selected and enriched data were created. Both types of data were analysed with these tools and outputs were thoroughly examined. Results An exploratory multivariate analysis of the most used tools for the enrichment of metabolite sets, based on a non-metric multidimensional scaling (NMDS) of Jaccard’s distances, was performed and mirrored their diversity. Codes (identifiers) of the metabolites of the datasets were searched in different metabolite databases (HMDB, KEGG, PubChem, ChEBI, BioCyc/HumanCyc, LipidMAPS, ChemSpider, METLIN and Recon2). The databases that presented more identifiers of the metabolites of the dataset were PubChem, followed by METLIN and ChEBI. However, these databases had duplicated entries and might present false positives. The performance of over-representation analysis (ORA) tools, including BioCyc/HumanCyc, ConsensusPathDB, IMPaLA, MBRole, MetaboAnalyst, Metabox, MetExplore, MPEA, PathVisio and Reactome and the mapping tool KEGGREST, was examined. Results were mostly consistent among tools and between real and enriched data despite the variability of the tools. Nevertheless, a few controversial results such as differences in the total number of metabolites were also found. Disease-based enrichment analyses were also assessed, but they were not found to be accurate probably due to the fact that metabolite disease sets are not up-to-date and the difficulty of predicting diseases from a list of metabolites. Conclusions We have extensively reviewed the state-of-the-art of the available range of tools for metabolomic datasets, the completeness of metabolite databases, the performance of ORA methods and disease-based analyses. Despite the variability of the tools, they provided consistent results independent of their analytic approach. However, more work on the completeness of metabolite and pathway databases is required, which strongly affects the accuracy of enrichment analyses. Improvements will be translated into more accurate and global insights of the metabolome. Electronic supplementary material The online version of this article (10.1186/s12859-017-2006-0) contains supplementary material, which is available to authorized users.
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              Opportunities and challenges in long-read sequencing data analysis

              Long-read technologies are overcoming early limitations in accuracy and throughput, broadening their application domains in genomics. Dedicated analysis tools that take into account the characteristics of long-read data are thus required, but the fast pace of development of such tools can be overwhelming. To assist in the design and analysis of long-read sequencing projects, we review the current landscape of available tools and present an online interactive database, long-read-tools.org, to facilitate their browsing. We further focus on the principles of error correction, base modification detection, and long-read transcriptomics analysis and highlight the challenges that remain.
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                Author and article information

                Journal
                Parasite
                Parasite
                parasite
                Parasite
                EDP Sciences
                1252-607X
                1776-1042
                2021
                12 April 2021
                : 28
                : ( publisher-idID: parasite/2021/01 )
                Affiliations
                [1 ] CONACYT-Instituto Tecnológico de Sonora Ciudad Obregón 85000 Sonora México
                [2 ] Departamento de Biotecnología y Ciencias Alimentarias, Instituto Tecnológico de Sonora Ciudad Obregón 85000 Sonora México
                [3 ] Departamento de Ciencias Agronómicas y Veterinarias, Instituto Tecnológico de Sonora Ciudad Obregón 85000 Sonora México
                Author notes
                [* ]Corresponding author: libia.rodriguez@ 123456conacyt.mx
                Article
                parasite200159 10.1051/parasite/2021033
                10.1051/parasite/2021033
                8040595
                33843581
                © L.Z. Rodriguez-Anaya et al., published by EDP Sciences, 2021

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Page count
                Figures: 2, Tables: 4, Equations: 0, References: 75, Pages: 15
                Funding
                Funded by: This research was financed by the National Council for Science and Technology (CONACYT) through the Cátedras CONACYT Program and the Frontiers of Science project.
                Award ID: Catedras CONCACYT Proyect ID "736"
                Award ID: Frontiers of Science project ID "840834"
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                Review Article

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