Assessing computational predictions of antimicrobial resistance phenotypes from microbial genomes.

The advent of rapid whole-genome sequencing has created new opportunities for computational prediction of antimicrobial resistance (AMR) phenotypes from genomic data. Both rule-based and machine learning (ML) approaches have been explored for this task, but systematic benchmarking is still needed. Here, we evaluated four state-of-the-art ML methods (Kover, PhenotypeSeeker, Seq2Geno2Pheno and Aytan-Aktug), an ML baseline and the rule-based ResFinder by training and testing each of them across 78 species-antibiotic datasets, using a rigorous benchmarking workflow that integrates three evaluation approaches, each paired with three distinct sample splitting methods. Our analysis revealed considerable variation in the performance across techniques and datasets. Whereas ML methods generally excelled for closely related strains, ResFinder excelled for handling divergent genomes. Overall, Kover most frequently ranked top among the ML approaches, followed by PhenotypeSeeker and Seq2Geno2Pheno. AMR phenotypes for antibiotic classes such as macrolides and sulfonamides were predicted with the highest accuracies. The quality of predictions varied substantially across species-antibiotic combinations, particularly for beta-lactams; across species, resistance phenotyping of the beta-lactams compound, aztreonam, amoxicillin/clavulanic acid, cefoxitin, ceftazidime and piperacillin/tazobactam, alongside tetracyclines demonstrated more variable performance than the other benchmarked antibiotics. By organism, Campylobacter jejuni and Enterococcus faecium phenotypes were more robustly predicted than those of Escherichia coli, Staphylococcus aureus, Salmonella enterica, Neisseria gonorrhoeae, Klebsiella pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii, Streptococcus pneumoniae and Mycobacterium tuberculosis. In addition, our study provides software recommendations for each species-antibiotic combination. It furthermore highlights the need for optimization for robust clinical applications, particularly for strains that diverge substantially from those used for training.

Engraftment of essential functions through multiple fecal microbiota transplants in chronic antibiotic-resistant pouchitis-a case study using metatranscriptomics.

BACKGROUND: Ileal pouch-anal anastomosis (IPAA) is the standard of care after total proctocolectomy for ulcerative colitis (UC). Around 50% of patients will experience pouchitis, an idiopathic inflammatory condition. Antibiotics are the backbone of treatment of pouchitis; however, antibiotic-resistant pouchitis develops in 5-10% of those patients. It has been shown that fecal microbiota transplantation (FMT) is an effective treatment for UC, but results for FMT antibiotic-resistant pouchitis are inconsistent. METHODS: To uncover which metabolic activities were transferred to the recipients during FMT and helped the remission, we performed a longitudinal case study of the gut metatranscriptomes from three patients and their donors. The patients were treated by two to three FMTs, and stool samples were analyzed for up to 140 days. RESULTS: Reduced expression in pouchitis patients compared to healthy donors was observed for genes involved in biosynthesis of amino acids, cofactors, and B vitamins. An independent metatranscriptome dataset of UC patients showed a similar result. Other functions including biosynthesis of butyrate, metabolism of bile acids, and tryptophan were also much lower expressed in pouchitis. After FMT, these activities transiently increased, and the overall metatranscriptome profiles closely mirrored those of the respective donors with notable fluctuations during the subsequent weeks. The levels of the clinical marker fecal calprotectin were concordant with the metatranscriptome data. Faecalibacterium prausnitzii represented the most active species contributing to butyrate synthesis via the acetyl-CoA pathway. Remission occurred after the last FMT in all patients and was characterized by a microbiota activity profile distinct from donors in two of the patients. CONCLUSIONS: Our study demonstrates the clear but short-lived activity engraftment of donor microbiota, particularly the butyrate biosynthesis after each FMT. The data suggest that FMT triggers shifts in the activity of patient microbiota towards health which need to be repeated to reach critical thresholds. As a case study, these insights warrant cautious interpretation, and validation in larger cohorts is necessary for generalized applications. In the long run, probiotics with high taxonomic diversity consisting of well characterized strains could replace FMT to avoid the costly screening of donors and the risk of transferring unwanted genetic material. Video Abstract.

Multi-omics analysis reveals the molecular response to heat stress in a "red tide" dinoflagellate.

BACKGROUND: "Red tides" are harmful algal blooms caused by dinoflagellate microalgae that accumulate toxins lethal to other organisms, including humans via consumption of contaminated seafood. These algal blooms are driven by a combination of environmental factors including nutrient enrichment, particularly in warm waters, and are increasingly frequent. The molecular, regulatory, and evolutionary mechanisms that underlie the heat stress response in these harmful bloom-forming algal species remain little understood, due in part to the limited genomic resources from dinoflagellates, complicated by the large sizes of genomes, exhibiting features atypical of eukaryotes. RESULTS: We present the de novo assembled genome (~ 4.75 Gbp with 85,849 protein-coding genes), transcriptome, proteome, and metabolome from Prorocentrum cordatum, a globally abundant, bloom-forming dinoflagellate. Using axenic algal cultures, we study the molecular mechanisms that underpin the algal response to heat stress, which is relevant to current ocean warming trends. We present the first evidence of a complementary interplay between RNA editing and exon usage that regulates the expression and functional diversity of biomolecules, reflected by reduction in photosynthesis, central metabolism, and protein synthesis. These results reveal genomic signatures and post-transcriptional regulation for the first time in a pelagic dinoflagellate. CONCLUSIONS: Our multi-omics analyses uncover the molecular response to heat stress in an important bloom-forming algal species, which is driven by complex gene structures in a large, high-G+C genome, combined with multi-level transcriptional regulation. The dynamics and interplay of molecular regulatory mechanisms may explain in part how dinoflagellates diversified to become some of the most ecologically successful organisms on Earth.

Critical Assessment of Metagenome Interpretation: the second round of challenges.

Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI II challenge engaged the community to assess methods on realistic and complex datasets with long- and short-read sequences, created computationally from around 1,700 new and known genomes, as well as 600 new plasmids and viruses. Here we analyze 5,002 results by 76 program versions. Substantial improvements were seen in assembly, some due to long-read data. Related strains still were challenging for assembly and genome recovery through binning, as was assembly quality for the latter. Profilers markedly matured, with taxon profilers and binners excelling at higher bacterial ranks, but underperforming for viruses and Archaea. Clinical pathogen detection results revealed a need to improve reproducibility. Runtime and memory usage analyses identified efficient programs, including top performers with other metrics. The results identify challenges and guide researchers in selecting methods for analyses.

Rapid and accurate identification of ribosomal RNA sequences via deep learning.

Advances in transcriptomic and translatomic techniques enable in-depth studies of RNA activity profiles and RNA-based regulatory mechanisms. Ribosomal RNA (rRNA) sequences are highly abundant among cellular RNA, but if the target sequences do not include polyadenylation, these cannot be easily removed in library preparation, requiring their post-hoc removal with computational techniques to accelerate and improve downstream analyses. Here, we describe RiboDetector, a novel software based on a Bi-directional Long Short-Term Memory (BiLSTM) neural network, which rapidly and accurately identifies rRNA reads from transcriptomic, metagenomic, metatranscriptomic, noncoding RNA, and ribosome profiling sequence data. Compared with state-of-the-art approaches, RiboDetector produced at least six times fewer misclassifications on the benchmark datasets. Importantly, the few false positives of RiboDetector were not enriched in certain Gene Ontology (GO) terms, suggesting a low bias for downstream functional profiling. RiboDetector also demonstrated a remarkable generalizability for detecting novel rRNA sequences that are divergent from the training data with sequence identities of <90%. On a personal computer, RiboDetector processed 40M reads in less than 6 min, which was ∼50 times faster in GPU mode and ∼15 times in CPU mode than other methods. RiboDetector is available under a GPL v3.0 license at https://github.com/hzi-bifo/RiboDetector.

Evaluating assembly and variant calling software for strain-resolved analysis of large DNA viruses.

Infection with human cytomegalovirus (HCMV) can cause severe complications in immunocompromised individuals and congenitally infected children. Characterizing heterogeneous viral populations and their evolution by high-throughput sequencing of clinical specimens requires the accurate assembly of individual strains or sequence variants and suitable variant calling methods. However, the performance of most methods has not been assessed for populations composed of low divergent viral strains with large genomes, such as HCMV. In an extensive benchmarking study, we evaluated 15 assemblers and 6 variant callers on 10 lab-generated benchmark data sets created with two different library preparation protocols, to identify best practices and challenges for analyzing such data. Most assemblers, especially metaSPAdes and IVA, performed well across a range of metrics in recovering abundant strains. However, only one, Savage, recovered low abundant strains and in a highly fragmented manner. Two variant callers, LoFreq and VarScan2, excelled across all strain abundances. Both shared a large fraction of false positive variant calls, which were strongly enriched in T to G changes in a 'G.G' context. The magnitude of this context-dependent systematic error is linked to the experimental protocol. We provide all benchmarking data, results and the entire benchmarking workflow named QuasiModo, Quasispecies Metric determination on omics, under the GNU General Public License v3.0 (https://github.com/hzi-bifo/Quasimodo), to enable full reproducibility and further benchmarking on these and other data.

Deep sequencing of biofilm microbiomes on dental composite materials.

Background: The microbiome on dental composites has not been studied in detail before. It has not been conclusively clarified whether restorative materials influence the oral microbiome. Methods: We used Illumina Miseq next-generation sequencing of the 16S V1-V2 region to compare the colonisation patterns of bovine enamel (BE) and the composite materials Grandio Flow (GF) and Grandio Blocs (GB) after 48 h in vivo in 14 volunteers. Applying a new method to maintain the oral microbiome ex vivo for 48 h also, we compared the microbiome on GF alone and with the new antimicrobial substance carolacton (GF+C). Results: All in vitro biofilm communities showed a higher diversity and richness than those grown in vivo but the very different atmospheric conditions must be considered. Contrary to expectations, there were only a few significant differences between BE and the composite materials GB and GF either in vivo or in vitro: Oribacterium, Peptostreptococcaceae [XI][G-1] and Streptococcus mutans were more prevalent and Megasphaera, Prevotella oulorum, Veillonella atypica, V. parvula, Gemella morbillorum, and Fusobacterium periodonticum were less prevalent on BE than on composites. In vivo, such preferences were only significant for Granulicatella adiacens (more prevalent on BE) and Fusobacterium nucleatum subsp. animalis (more prevalent on composites). On DNA sequence level, there were no significant differences between the biofilm communities on GF and GF+C. Conclusion: We found that the oral microbiome showed an increased richness when grown on various composites compared to BE in vitro, but otherwise changed only slightly independent of the in vivo or in vitro condition. Our new ex vivo biofilm model might be useful for pre-clinical testing of preventive strategies.

Metatranscriptome Analysis of the Vaginal Microbiota Reveals Potential Mechanisms for Protection against Metronidazole in Bacterial Vaginosis.

Bacterial vaginosis (BV) is a prevalent multifactorial disease of women in their reproductive years characterized by a shift from the Lactobacillus species-dominated microbial community toward a taxonomically diverse anaerobic community. For unknown reasons, some women do not respond to therapy. In our recent clinical study, among 37 women diagnosed with BV, 31 were successfully treated with metronidazole, while 6 still had BV after treatment. To discover possible reasons for the lack of response in those patients, we performed a metatranscriptome analysis of their vaginal microbiota, comparing them to the patients who responded. Seven of 8 clustered regularly interspaced short palindromic repeat (CRISPR)-associated (Cas) genes of Gardnerella vaginalis were highly upregulated in nonresponding patients. Cas genes, in addition to protecting against phages, might be involved in DNA repair, thus mitigating the bactericidal effect of DNA-damaging agents such as metronidazole. In the second part of our study, we analyzed the vaginal metatranscriptomes of four patients over 3 months and showed high in vivo expression of genes for pore-forming toxins in L. iners and of genes encoding enzymes for the production of hydrogen peroxide and d-lactate in L. crispatusIMPORTANCE Bacterial vaginosis is a serious issue for women in their reproductive years. Although it can usually be cured by antibiotics, the recurrence rate is very high, and some women do not respond to antibiotic therapy. The reasons for that are not known. Therefore, we undertook a study to detect the activity of the complete microbiota in the vaginal fluid of women who responded to antibiotic therapy and compared it to the activity of the microbiota in women who did not respond. We found that one of the most important pathogens in bacterial vaginosis, Gardnerella vaginalis, has activated genes that can repair the DNA damage caused by the antibiotic in those women that do not respond to therapy. Suppressing these genes might be a possibility to improve the antibiotic therapy of bacterial vaginosis.

Worlds Apart - Transcriptome Profiles of Key Oral Microbes in the Periodontal Pocket Compared to Single Laboratory Culture Reflect Synergistic Interactions.

Periodontitis is a worldwide prevalent oral disease which results from dysbiosis of the periodontal microbiome. Some of the most active microbial players, e.g., Porphyromonas gingivalis, Treponema denticola, and Fusobacterium nucleatum, have extensively been studied in the laboratory, but it is unclear to which extend these findings can be transferred to in vivo conditions. Here we show that the transcriptional profiles of P. gingivalis, T. denticola, and F. nucleatum in the periodontal niche are distinct from those in single laboratory culture and exhibit functional similarities. GO (gene ontology) term enrichment analysis showed up-regulation of transporters, pathogenicity related traits and hemin/heme uptake mechanisms for all three species in vivo. Differential gene expression analysis revealed that cysteine proteases, transporters and hemin/heme-binding proteins were highly up-regulated in the periodontal niche, while genes involved in DNA modification were down-regulated. The data suggest strong interactions between those three species regarding protein degradation, iron up-take, and mobility in vivo, explaining their enhanced synergistic pathogenicity. We discovered a strikingly high frequency of Single Nucleotide Polymorphisms (SNPs) in vivo. For F. nucleatum we discovered a total of 127,729 SNPs in periodontal niche transcripts, which were found in similar frequency in health and disease and covered the entire genome, suggesting continuous evolution in the host. We conclude that metabolic interactions shape gene expression in vivo. Great caution is required when inferring pathogenicity of microbes from laboratory data, and microdiversity is an important adaptive trait of natural communities.

Treatment of biofilms in bacterial vaginosis by an amphoteric tenside pessary-clinical study and microbiota analysis.

BACKGROUND: Bacterial vaginosis (BV) is the most common vaginal syndrome among women in their reproductive years. It is associated with an increased risk of acquiring sexually transmitted infections and complications like preterm labor. BV is characterized by a high recurrence rate for which biofilms frequently found on vaginal epithelial cells may be a reason. RESULTS: Here, we report a controlled randomized clinical trial that tested the safety and effectiveness of a newly developed pessary containing an amphoteric tenside (WO3191) to disrupt biofilms after metronidazole treatment of BV. Pessaries containing lactic acid were provided to the control group, and microbial community composition was determined via Illumina sequencing of the V1-V2 region of the 16S rRNA gene. The most common community state type (CST) in healthy women was characterized by Lactobacillus crispatus. In BV, diversity was high with communities dominated by either Lactobacillus iners, Prevotella bivia, Sneathia amnii, or Prevotella amnii. Women with BV and proven biofilms had an increased abundance of Sneathia sanguinegens and a decreased abundance of Gardnerella vaginalis. Following metronidazole treatment, clinical symptoms cleared, Nugent score shifted to Lactobacillus dominance, biofilms disappeared, and diversity (Shannon index) was reduced in most women. Most of the patients responding to therapy exhibited a L. iners CST. Treatment with WO 3191 reduced biofilms but did not prevent recurrence. Women with high diversity after antibiotic treatment were more likely to develop recurrence. CONCLUSIONS: Stabilizing the low diversity healthy flora by promoting growth of health-associated Lactobacillus sp. such as L. crispatus may be beneficial for long-term female health. TRIAL REGISTRATION: ClinicalTrials.gov NCT02687789.

The urinary microbiota of men and women and its changes in women during bacterial vaginosis and antibiotic treatment.

BACKGROUND: The urinary microbiota is similarly complex as the vaginal and penile microbiota, yet its role as a reservoir for pathogens and for recurrent polymicrobial biofilm diseases like bacterial vaginosis (BV) is not clear. RESULTS: Here, we analysed the urinary microbiota of healthy men and women and compared it with that of women during BV and after antibiotic treatment using next-generation sequencing of the 16S rRNA gene V1-V2 regions. Eight different community types, so called urotypes (UT), were identified in healthy humans, all of which were shared between men and women, except UT 7, dominated in relative abundance by Lactobacillus crispatus, which was found in healthy women only. Orally applied metronidazole significantly reduced Shannon diversity and the mean relative abundance of Gardnerella vaginalis, Atopobium vaginae, and Sneathia amnii, while L. iners increased to levels twofold higher than those found in healthy women. Although individual urine microbial profiles strongly responded to the antibiotic, the healthy community could not be restored. The correlation between urinary and vaginal fluid microbiota was generally weak and depending on UT and BV status. It was highest in UT 1 in acute BV (59% of samples), but after metronidazole treatment, only 3 out of 35 women showed a significant correlation between their urinary and vaginal microbiota composition. CONCLUSIONS: Urethra and bladder thus harbor microbial communities distinct from the vagina. The high abundance of BV related species in the urine of both men and women suggests that urine may act as a reservoir of pathogens and contribute to recurrence. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02687789.

Dysbiosis in chronic periodontitis: Key microbial players and interactions with the human host.

Periodontitis is an extremely prevalent disease worldwide and is driven by complex dysbiotic microbiota. Here we analyzed the transcriptional activity of the periodontal pocket microbiota from all domains of life as well as the human host in health and chronic periodontitis. Bacteria showed strong enrichment of 18 KEGG functional modules in chronic periodontitis, including bacterial chemotaxis, flagellar assembly, type III secretion system, type III CRISPR-Cas system, and two component system proteins. Upregulation of these functions was driven by the red-complex pathogens and candidate pathogens, e.g. Filifactor alocis, Prevotella intermedia, Fretibacterium fastidiosum and Selenomonas sputigena. Nine virulence factors were strongly up-regulated, among them the arginine deiminase arcA from Porphyromonas gingivalis and Mycoplasma arginini. Viruses and archaea accounted for about 0.1% and 0.22% of total putative mRNA reads, respectively, and a protozoan, Entamoeba gingivalis, was highly enriched in periodontitis. Fourteen human transcripts were enriched in periodontitis, including a gene for a ferric iron binding protein, indicating competition with the microbiota for iron, and genes associated with cancer, namely nucleolar phosphoprotein B23, ankyrin-repeat domain 30B-like protein and beta-enolase. The data provide evidence on the level of gene expression in vivo for the potentially severe impact of the dysbiotic microbiota on human health.

Quorum sensing of Streptococcus mutans is activated by Aggregatibacter actinomycetemcomitans and by the periodontal microbiome.

BACKGROUND: The oral cavity is inhabited by complex microbial communities forming biofilms that can cause caries and periodontitis. Cell-cell communication might play an important role in modulating the physiologies of individual species, but evidence so far is limited. RESULTS: Here we demonstrate that a pathogen of the oral cavity, Aggregatibacter actinomycetemcomitans (A. act.), triggers expression of the quorum sensing (QS) regulon of Streptococcus mutans, a well-studied model organism for cariogenic streptococci, in dual-species biofilms grown on artificial saliva. The gene for the synthesis of the QS signal XIP is essential for this interaction. Transcriptome sequencing of biofilms revealed that S. mutans up-regulated the complete QS regulon (transformasome and mutacins) in the presence of A. act. and down-regulated oxidative stress related genes. A.act. required the presence of S. mutans for growth. Fimbriae and toxins were its most highly expressed genes and up-regulation of anaerobic metabolism, chaperones and iron acquisition genes was observed in co-culture. Metatranscriptomes from periodontal pockets showed highly variable levels of S. mutans and low levels of A. act.. Transcripts of the alternative sigma-factor SigX, the key regulator of QS in S. mutans, were significantly enriched in periodontal pockets compared to single cultures (log2 4.159, FDR ≤0.001, and expression of mutacin related genes and transformasome components could be detected. CONCLUSION: The data show that the complete QS regulon of S. mutans can be induced by an unrelated oral pathogen and S. mutans may be competent in oral biofilms in vivo.

Bacterioplankton Biogeography of the Atlantic Ocean: A Case Study of the Distance-Decay Relationship.

In order to determine the influence of geographical distance, depth, and Longhurstian province on bacterial community composition and compare it with the composition of photosynthetic micro-eukaryote communities, 382 samples from a depth-resolved latitudinal transect (51°S-47°N) from the epipelagic zone of the Atlantic ocean were analyzed by Illumina amplicon sequencing. In the upper 100 m of the ocean, community similarity decreased toward the equator for 6000 km, but subsequently increased again, reaching similarity values of 40-60% for samples that were separated by ~12,000 km, resulting in a U-shaped distance-decay curve. We conclude that adaptation to local conditions can override the linear distance-decay relationship in the upper epipelagial of the Atlantic Ocean which is apparently not restrained by barriers to dispersal, since the same taxa were shared between the most distant communities. The six Longhurstian provinces covered by the transect were comprised of distinct microbial communities; ~30% of variation in community composition could be explained by province. Bacterial communities belonging to the deeper layer of the epipelagic zone (140-200 m) lacked a distance-decay relationship altogether and showed little provincialism. Interestingly, those biogeographical patterns were consistently found for bacteria from three different size fractions of the plankton with different taxonomic composition, indicating conserved underlying mechanisms. Analysis of the chloroplast 16S rRNA gene sequences revealed that phytoplankton composition was strongly correlated with both free-living and particle associated bacterial community composition (R between 0.51 and 0.62, p < 0.002). The data show that biogeographical patterns commonly found in macroecology do not hold for marine bacterioplankton, most likely because dispersal and evolution occur at drastically different rates in bacteria.

Co-occurrence Analysis of Microbial Taxa in the Atlantic Ocean Reveals High Connectivity in the Free-Living Bacterioplankton.

We determined the taxonomic composition of the bacterioplankton of the epipelagic zone of the Atlantic Ocean along a latitudinal transect (51°S-47°N) using Illumina sequencing of the V5-V6 region of the 16S rRNA gene and inferred co-occurrence networks. Bacterioplankon community composition was distinct for Longhurstian provinces and water depth. Free-living microbial communities (between 0.22 and 3 µm) were dominated by highly abundant and ubiquitous taxa with streamlined genomes (e.g., SAR11, SAR86, OM1, Prochlorococcus) and could clearly be separated from particle-associated communities which were dominated by Bacteroidetes, Planktomycetes, Verrucomicrobia, and Roseobacters. From a total of 369 different communities we then inferred co-occurrence networks for each size fraction and depth layer of the plankton between bacteria and between bacteria and phototrophic micro-eukaryotes. The inferred networks showed a reduction of edges in the deepest layer of the photic zone. Networks comprised of free-living bacteria had a larger amount of connections per OTU when compared to the particle associated communities throughout the water column. Negative correlations accounted for roughly one third of the total edges in the free-living communities at all depths, while they decreased with depth in the particle associated communities where they amounted for roughly 10% of the total in the last part of the epipelagic zone. Co-occurrence networks of bacteria with phototrophic micro-eukaryotes were not taxon-specific, and dominated by mutual exclusion (~60%). The data show a high degree of specialization to micro-environments in the water column and highlight the importance of interdependencies particularly between free-living bacteria in the upper layers of the epipelagic zone.

Low diversity of planktonic bacteria in the tropical ocean.

The diversity of macro-organisms increases towards the equator, with almost no exceptions. It is the most conserved biogeographical pattern on earth and is thought to be related to the increase of temperature and productivity in the tropics. The extent and orientation of a latitudinal gradient of marine bacterioplankton diversity is controversial. Here we studied the euphotic zone of the Atlantic Ocean based on a transect covering ~12.000 km from 51°S to 47 °N. Water samples were collected at 26 stations at five depths between 20 and 200 m and sequentially filtered through 8 µm, 3 µm and 0,22 µm filters, resulting in a total of 359 samples. Illumina sequencing of the V5-V6 region of the 16S rRNA gene revealed a clear biogeographic pattern with a double inverted latitudinal gradient. Diversity was higher in mid-latitudinal regions of the Atlantic Ocean and decreased towards the equator. This pattern was conserved for bacteria from all three planktonic size fractions. Diversity showed a non-linear relationship with temperature and was negatively correlated with bacterial cell numbers in the upper depth layers (<100 m). The latitudinal gradients of marine bacterial diversity and the mechanisms that govern them are distinct from those found in macro-organisms.

Construction of a genome-scale metabolic network of the plant pathogen Pectobacterium carotovorum provides new strategies for bactericide discovery.

We reconstructed the first genome-scale metabolic network of the plant pathogen Pectobacterium carotovorum subsp. carotovorum PC1 based on its genomic sequence, annotation, and physiological data. Metabolic characteristics were analyzed using flux balance analysis (FBA), and the results were afterwards validated by phenotype microarray (PM) experiments. The reconstructed genome-scale metabolic model, iPC1209, contains 2235 reactions, 1113 metabolites and 1209 genes. We identified 19 potential bactericide targets through a comprehensive in silico gene-deletion study. Next, we performed virtual screening to identify candidate inhibitors for an important potential drug target, alkaline phosphatase, and experimentally verified that three lead compounds were able to inhibit both bacterial cell viability and the activity of alkaline phosphatase in vitro. This study illustrates a new strategy for the discovery of agricultural bactericides.

Functional biomarkers for chronic periodontitis and insights into the roles of Prevotella nigrescens and Fusobacterium nucleatum; a metatranscriptome analysis.

BACKGROUND/OBJECTIVES: Periodontitis is the most prevalent inflammatory disease worldwide and is caused by a dysbiotic subgingival biofilm. Here we used metatranscriptomics to determine the functional shift from health to periodontitis, the response of individual species to dysbiosis and to discover biomarkers. METHODS: Sixteen individuals were studied, from which six were diagnosed with chronic periodontitis. Illumina sequencing of the total messenger RNA (mRNA) yielded ~42 million reads per sample. A total of 324 human oral taxon phylotypes and 366,055 open reading frames from the HOMD database reference genomes were detected. RESULTS: The transcriptionally active community shifted from Bacilli and Actinobacteria in health to Bacteroidia, Deltaproteobacteria, Spirochaetes and Synergistetes in periodontitis. Clusters of orthologous groups (COGs) related to carbohydrate transport and catabolism dominated in health, whereas protein degradation and amino acid catabolism dominated in disease. The LEfSe, random forest and support vector machine methods were applied to the 2,000 most highly expressed genes and discovered the three best functional biomarkers, namely haem binding protein HmuY from Porphyromonas gingivalis, flagellar filament core protein FlaB3 from Treponema denticola, and repeat protein of unknown function from Filifactor alocis. They predicted the diagnosis correctly for 14 from 16 individuals, and when applied to an independent study misclassified one out of six subjects only. Prevotella nigrescens shifted from commensalism to virulence by upregulating the expression of metalloproteases and the haem transporter. Expression of genes for the synthesis of the cytotoxic short-chain fatty acid butyrate was observed by Fusobacterium nucleatum under all conditions. Four additional species contributed to butyrate synthesis in periodontitis and they used an additional pathway. CONCLUSION: Gene biomarkers of periodontitis are highly predictive. The pro-inflammatory role of F. nucelatum is not related to butyrate synthesis.

RBRDetector: improved prediction of binding residues on RNA-binding protein structures using complementary feature- and template-based strategies.

Computational prediction of RNA-binding residues is helpful in uncovering the mechanisms underlying protein-RNA interactions. Traditional algorithms individually applied feature- or template-based prediction strategy to recognize these crucial residues, which could restrict their predictive power. To improve RNA-binding residue prediction, herein we propose the first integrative algorithm termed RBRDetector (RNA-Binding Residue Detector) by combining these two strategies. We developed a feature-based approach that is an ensemble learning predictor comprising multiple structure-based classifiers, in which well-defined evolutionary and structural features in conjunction with sequential or structural microenvironment were used as the inputs of support vector machines. Meanwhile, we constructed a template-based predictor to recognize the putative RNA-binding regions by structurally aligning the query protein to the RNA-binding proteins with known structures. The final RBRDetector algorithm is an ingenious fusion of our feature- and template-based approaches based on a piecewise function. By validating our predictors with diverse types of structural data, including bound and unbound structures, native and simulated structures, and protein structures binding to different RNA functional groups, we consistently demonstrated that RBRDetector not only had clear advantages over its component methods, but also significantly outperformed the current state-of-the-art algorithms. Nevertheless, the major limitation of our algorithm is that it performed relatively well on DNA-binding proteins and thus incorrectly predicted the DNA-binding regions as RNA-binding interfaces. Finally, we implemented the RBRDetector algorithm as a user-friendly web server, which is freely accessible at http://ibi.hzau.edu.cn/rbrdetector.