A supervised Bayesian factor model for the identification of multi-omics signatures.

MOTIVATION: Predictive biological signatures provide utility as biomarkers for disease diagnosis and prognosis, as well as prediction of responses to vaccination or therapy. These signatures are identified from high-throughput profiling assays through a combination of dimensionality reduction and machine learning techniques. The genes, proteins, metabolites, and other biological analytes that compose signatures also generate hypotheses on the underlying mechanisms driving biological responses, thus improving biological understanding. Dimensionality reduction is a critical step in signature discovery to address the large number of analytes in omics datasets, especially for multi-omics profiling studies with tens of thousands of measurements. Latent factor models, which can account for the structural heterogeneity across diverse assays, effectively integrate multi-omics data and reduce dimensionality to a small number of factors that capture correlations and associations among measurements. These factors provide biologically interpretable features for predictive modeling. However, multi-omics integration and predictive modeling are generally performed independently in sequential steps, leading to suboptimal factor construction. Combining these steps can yield better multi-omics signatures that are more predictive while still being biologically meaningful. RESULTS: We developed a supervised variational Bayesian factor model that extracts multi-omics signatures from high-throughput profiling datasets that can span multiple data types. Signature-based multiPle-omics intEgration via lAtent factoRs (SPEAR) adaptively determines factor rank, emphasis on factor structure, data relevance and feature sparsity. The method improves the reconstruction of underlying factors in synthetic examples and prediction accuracy of coronavirus disease 2019 severity and breast cancer tumor subtypes. AVAILABILITY AND IMPLEMENTATION: SPEAR is a publicly available R-package hosted at https://bitbucket.org/kleinstein/SPEAR.

Hearing Loss Prevalence, Years Lived With Disability, and Hearing Aid Use in the United States From 1990 to 2019: Findings From the Global Burden of Disease Study.

OBJECTIVES: This article describes key data sources and methods used to estimate hearing loss in the United States, in the Global Burden of Disease study. Then, trends in hearing loss are described for 2019, including temporal trends from 1990 to 2019, changing prevalence over age, severity patterns, and utilization of hearing aids. DESIGN: We utilized population-representative surveys from the United States to estimate hearing loss prevalence for the Global Burden of Disease study. A key input data source in modeled estimates are the National Health and Nutrition Examination Surveys (NHANES), years 1988 to 2010. We ran hierarchical severity-specific models to estimate hearing loss prevalence. We then scaled severity-specific models to sum to total hearing impairment prevalence, adjusted estimates for hearing aid coverage, and split estimates by etiology and tinnitus status. We computed years lived with disability (YLDs), which quantifies the amount of health loss associated with a condition depending on severity and creates a common metric to compare the burden of disparate diseases. This was done by multiplying the prevalence of severity-specific hearing loss by corresponding disability weights, with additional weighting for tinnitus comorbidity. RESULTS: An estimated 72.88 million (95% uncertainty interval (UI) 68.53 to 77.30) people in the United States had hearing loss in 2019, accounting for 22.2% (20.9 to 23.6) of the total population. Hearing loss was responsible for 2.24 million (1.56 to 3.11) YLDs (3.6% (2.8 to 4.7) of total US YLDs). Age-standardized prevalence was higher in males (17.7% [16.7 to 18.8]) compared with females (11.9%, [11.2 to 12.5]). While most cases of hearing loss were mild (64.3%, 95% UI 61.0 to 67.6), disability was concentrated in cases that were moderate or more severe. The all-age prevalence of hearing loss in the United States was 28.1% (25.7 to 30.8) higher in 2019 than in 1990, despite stable age-standardized prevalence. An estimated 9.7% (8.6 to 11.0) of individuals with mild to profound hearing loss utilized a hearing aid, while 32.5% (31.9 to 33.2) of individuals with hearing loss experienced tinnitus. Occupational noise exposure was responsible for 11.2% (10.2 to 12.4) of hearing loss YLDs. CONCLUSIONS: Results indicate large burden of hearing loss in the United States, with an estimated 1 in 5 people experiencing this condition. While many cases of hearing loss in the United States were mild, growing prevalence, low usage of hearing aids, and aging populations indicate the rising impact of this condition in future years and the increasing importance of domestic access to hearing healthcare services. Large-scale audiometric surveys such as NHANES are needed to regularly assess hearing loss burden and access to healthcare, improving our understanding of who is impacted by hearing loss and what groups are most amenable to intervention.

Probiotics: insights and new opportunities for Clostridioides difficile intervention.

Clostridioides difficile infection (CDI) is a life-threatening disease caused by the Gram-positive, opportunistic intestinal pathogen C. difficile. Despite the availability of antimicrobial drugs to treat CDI, such as vancomycin, metronidazole, and fidaxomicin, recurrence of infection remains a significant clinical challenge. The use of live commensal microorganisms, or probiotics, is one of the most investigated non-antibiotic therapeutic options to balance gastrointestinal (GI) microbiota and subsequently tackle dysbiosis. In this review, we will discuss major commensal probiotic strains that have the potential to prevent and/or treat CDI and its recurrence, reassess the efficacy of probiotics supplementation as a CDI intervention, delve into lessons learned from probiotic modulation of the immune system, explore avenues like genome-scale metabolic network reconstructions, genome sequencing, and multi-omics to identify novel strains and understand their functionality, and discuss the current regulatory framework, challenges, and future directions.

Evaluating the effect and user satisfaction of an adapted and translated mobile health application ASTHMAXcel© among adults with asthma in Pune, India.

OBJECTIVE: ASTHMAXcel© is a mobile application previously shown to improve asthma knowledge, control, and quality of life. In this study, we translated the application to Marathi for pilot testing in Pune, India in order to evaluate its impact on user satisfaction and asthma knowledge among adult asthma patients. METHODS: ASTHMAXcel© was adapted to Marathi with the help of asthma patients and clinicians from Bharati Hospital. 57 different asthma patients were then recruited and received the Asthma Knowledge Questionnaire (AKQ), Asthma Control Questionnaire (ACQ), and Mini Asthma Quality of Life Questionnaire (Mini-AQLQ) to complete at baseline. Study participants then completed the adapted ASTHMAXcel© application. Post-intervention, participants filled out a post-AKQ and Questionnaire for User Interface Satisfaction (QUIS). A subset of participants was also interviewed for qualitative feedback. Paired t-tests and Pearson's correlation were used for statistical analysis. RESULTS: Mean AKQ improved from 5.0+/-2.4 to 12.4+/-1.6 (p = 0.0001). QUIS results revealed that participants were highly satisfied with the application, scoring an average of 50 out of 54 maximum points. Better baseline asthma control was correlated with greater overall experience with the application (-0.110, p = 0.0417). Finally, the qualitative feedback revealed four themes for future refinement. CONCLUSION: The adapted version of ASTHMAXcel© was linked to significant improvement in patient asthma knowledge and a high level of user satisfaction. These results support the potential utility of mHealth applications in promoting guideline-based asthma care in India. However, further studies are needed to establish a causal relationship between ASTHMAXcel© and improved clinical outcomes.

Scoring System for the Use of Nebulizers in the Primary Care Settings: An Expert Consensus Statement.

BACKGROUND: The use of nebulizers is an important and useful method for delivering drugs to the lungs in patients with various airway and lung parenchymal disorders. They are primarily used in patients with acute symptoms and in a selected group of patients for maintenance treatment. Its use has increased, especially during the coronavirus disease 2019 (COVID-19) pandemic. To ensure the appropriate use of nebulizers by primary care physicians and to guide them, we aimed to develop a simple nebulizer use score. METHODS: An expert working group (EWG) of pulmonologists were formed who using a semi- Delphi method, developed a list of variables and a cut-off score to decide when to use nebulizers. We started with a total of 55 variables that were developed through an exhaustive review of the literature. These were further reduced to smaller numbers that had the maximum score as well as concordance with the EWG. The scores ranged from 1 to 10 (completely disagree to completely agree), and only those above 7.5 were selected. RESULTS: A total of 8 variables with the highest scores were selected (Table 1), which had a total maximum score of 40. A score of <15 was suggested to indicate no use of nebulizer and >20 to suggest definite use of nebulizer. A score between 15 and 20 was suggested for physician judgment. A separate table of 12 conditions was made where the use of nebulizers was mandatory. CONCLUSION: This first-of-its-kind nebulizer score can be used by primary care physicians to decide which patients should be put on nebulizer treatment.

LinkedImm: a linked data graph database for integrating immunological data.

BACKGROUND: Many systems biology studies leverage the integration of multiple data types (across different data sources) to offer a more comprehensive view of the biological system being studied. While SQL (Structured Query Language) databases are popular in the biomedical domain, NoSQL database technologies have been used as a more relationship-based, flexible and scalable method of data integration. RESULTS: We have created a graph database integrating data from multiple sources. In addition to using a graph-based query language (Cypher) for data retrieval, we have developed a web-based dashboard that allows users to easily browse and plot data without the need to learn Cypher. We have also implemented a visual graph query interface for users to browse graph data. Finally, we have built a prototype to allow the user to query the graph database in natural language. CONCLUSION: We have demonstrated the feasibility and flexibility of using a graph database for storing and querying immunological data with complex biological relationships. Querying a graph database through such relationships has the potential to discover novel relationships among heterogeneous biological data and metadata.

Hemoglobin Induces Early and Robust Biofilm Development in Streptococcus pneumoniae by a Pathway That Involves comC but Not the Cognate comDE Two-Component System.

Streptococcus pneumoniae grows in biofilms during both asymptomatic colonization and infection. Pneumococcal biofilms on abiotic surfaces exhibit delayed growth and lower biomass and lack the structures seen on epithelial cells or during nasopharyngeal carriage. We show here that adding hemoglobin to the medium activated unusually early and vigorous biofilm growth in multiple S. pneumoniae serotypes grown in batch cultures on abiotic surfaces. Human blood (but not serum, heme, or iron) also stimulated biofilms, and the pore-forming pneumolysin, ply, was required for this induction. S. pneumoniae transitioning from planktonic into sessile growth in the presence of hemoglobin displayed an extensive transcriptome remodeling within 1 and 2 h. Differentially expressed genes included those involved in the metabolism of carbohydrates, nucleotides, amino acid, and lipids. The switch into adherent states also influenced the expression of several regulatory systems, including the comCDE genes. Inactivation of comC resulted in 67% reduction in biofilm formation, while the deletion of comD or comE had limited or no effect, respectively. These observations suggest a novel route for CSP-1 signaling independent of the cognate ComDE two-component system. Biofilm induction and the associated transcriptome remodeling suggest hemoglobin serves as a signal for host colonization in pneumococcus.

Description and genomic insights into a multidrug resistant novel bacterium Savagea serpentis sp. nov., isolated from the scats of a vine snake (Ahaetulla nasuta).

Two Gram-stain positive, endospore forming, non-motile, rod shaped bacterial strains SN6T and SN6b were isolated from scats of a mildly venomous vine snake (Ahaetulla nasuta). Strains were phenotypically resistant to multiple antibiotics of four different classes i.e. aminoglycosides, ß-lactams, fluoroquinolones and sulphonamides. Cells of both the strains were catalase positive and oxidase negative. Phylogenetic analysis based on 16S rRNA gene sequence analysis of these two strains showed closest similarity (99.2% and 99.3%) with Savagea faecisuis Con12T, the only species of the genus Savagea and ≤ 94.9% with the species of other closest genera of the family Planococcaceae. The 16S rRNA gene sequence similarity (99%), DNA-DNA relatedness (95%) and similar phenotypic characteristics between the strains SN6T and SN6b revealed their phylogenetic affiliation to the same species. Hence, strain SN6b is an additional strain of the type strain SN6T. DNA-DNA relatedness of strain SN6T with S. faecisuis Con12T was 32.8%. Predominant fatty acids were iso-C15:0 (32.0%), iso-C16:1 ω11c (19.2%) and iso-C17:1 ω10c (12.1%). MK-6 (100%) was the only respiratory quinone of strain SN6T. Diphosphatidylglycerol, phosphatidylglycerol and phosphatidylethanolamine were the major polar lipids. Cell wall peptidoglycan was A4α; L-Lys-Gly-D-Glu type. The DNA G + C content (mol%) of SN6T was 40.8. Whole genome sequence of SN6T consisted of 26,37,389 base pairs in length with 2667 annotated genes, out of which 1021 corresponds to hypothetical proteins and 1646 with functional assignments including antibiotic resistance, multidrug resistance efflux pumps, invasion and virulence factors. Comparative polyphasic study of the strains SN6T, SN6b and S. faecisuis Con12T elucidated the differentiating characteristics which led to describing strain SN6T and SN6b as a novel species of the genus Savagea for which the name Savagea serpentis sp. nov is proposed. The type strain of Savagea serpentis is SN6T (= KCTC 33546T = CCUG 6786T).

Integrated Genomic and Functional Characterization of the Anti-diabetic Potential of Arthrobacter sp. SW1.

For decades, bacterial natural products have served as valuable resources for developing novel drugs to treat several human diseases. Recent advancements in the integrative approach of using genomic and functional tools have proved beneficial in obtaining a comprehensive understanding of these biomolecules. This study presents an in-depth characterization of the anti-diabetic activity exhibited by a bacterial isolate SW1, isolated from an effluent treatment plant. As a primary screening, we assessed the isolate for its potential to inhibit alpha-amylase and alpha-glucosidase enzymes. Upon confirmation, we further utilized LC-MS, ESI-MS/MS, and NMR spectroscopy to identify and characterize the biomolecule. These efforts were coupled with the genomic assessment of the biosynthetic gene cluster involved in the anti-diabetic compound production. Our investigation discovered that the isolate SW1 inhibited both α-amylase and α-glucosidase activity. The chemical analysis suggested the production of acarbose, an anti-diabetic biomolecule, which was further confirmed by the presence of biosynthetic gene cluster "acb" in the genome. Our in-depth chemical characterization and genome mining approach revealed the potential of bacteria from an unconventional niche, an effluent treatment plant. To the best of our knowledge, it is one of the first few reports of acarbose production from the genus Arthrobacter.

Comparative genomics of whole-cell pertussis vaccine strains from India.

BACKGROUND: Despite high vaccination coverage using acellular (ACV) and whole-cell pertussis (WCV) vaccines, the resurgence of pertussis is observed globally. Genetic divergence in circulating strains of Bordetella pertussis has been reported as one of the contributing factors for the resurgence of the disease. Our current knowledge of B. pertussis genetic evolution in circulating strains is mostly based on studies conducted in countries using ACVs targeting only a few antigens used in the production of ACVs. To better understand the adaptation to vaccine-induced selection pressure, it will be essential to study B. pertussis populations in developing countries which are using WCVs. India is a significant user and global supplier of WCVs. We report here comparative genome analyses of vaccine and clinical isolates reported from India. Whole-genome sequences obtained from vaccine strains: WCV (J445, J446, J447 and J448), ACV (BP165) were compared with Tohama-I reference strain and recently reported clinical isolates from India (BPD1, BPD2). Core genome-based phylogenetic analysis was also performed using 166 isolates reported from countries using ACV. RESULTS: Whole-genome analysis of vaccine and clinical isolates reported from India revealed high genetic similarity and conserved genome among strains. Phylogenetic analysis showed that clinical and vaccine strains share genetic closeness with reference strain Tohama-I. The allelic profile of vaccine strains (J445:ptxP1/ptxA2/prn1/fim2-1/fim3-1; J446: ptxP2/ptxA4/prn7/fim2-2/fim3-1; J447 and J448: ptxP1/ptxA1/ prn1/fim2-1/fim3-1), which matched entirely with clinical isolates (BPD1:ptxP1/ptxA1/prn1/fim2-1 and BPD2: ptxP1/ptxA1/prn1/fim2-1) reported from India. Multi-locus sequence typing (MLST) demonstrated the presence of dominant sequence types ST2 and primitive ST1 in vaccine strains which will allow better coverage against circulating strains of B. pertussis. CONCLUSIONS: The study provides a detailed characterization of vaccine and clinical strains reported from India, which will further facilitate epidemiological studies on genetic shifts in countries which are using WCVs in their immunization programs.

Structural studies of antiviral inhibitor with HIV-1 protease bearing drug resistant substitutions of V32I, I47V and V82I.

HIV-1 protease inhibitors are effective in HIV/AIDS therapy, although drug resistance is a severe problem. This study examines the effects of four investigational inhibitors against HIV-1 protease with drug resistant mutations of V32I, I47V and V82I (PRTri) that model the inhibitor-binding site of HIV-2 protease. These inhibitors contain diverse chemical modifications on the darunavir scaffold and form new interactions with wild type protease, however, the measured inhibition constants for PRTri mutant range from 17 to 40 nM or significantly worse than picomolar values reported for wild type enzyme. The X-ray crystal structure of PRTri mutant in complex with inhibitor 1 at 1.5 Šresolution shows minor changes in interactions with inhibitor compared with the corresponding wild type PR complex. Instead, the basic amine at P2 of inhibitor together with mutation V82I induces two alternate conformations for the side chain of Arg8 with new interactions with inhibitor and Leu10. Hence, inhibition is influenced by small coordinated changes in hydrophobic interactions.

Curcumin in combination with anti-cancer drugs: A nanomedicine review.

A huge surge of research is being conducted on combination therapy with anticancer compounds formulated in the form of nanoparticles (NPs). Numerous advantages like dose minimalization and synergism, reversal of multi drug resistance (MDRs), enhanced efficacy have emerged with nanoencapsulation of chemotherapeutic agents with chemo-sensitizing agent like curcumin. Within last couple of years various nano-sized formulations have been designed and tested both in vitro with cell lines for different types of cancers and in vivo with cancer types and drug resistance models. Despite the combinatorial models being advanced, translation to human trials has not been as smooth as one would have hoped, with as few as twenty ongoing clinical trials with curcumin combination, with less than 1/10th being nano-particulate formulations. Mass production of nano-formulation based on their physico-chemical and pharmacokinetics deficits poses as major hurdle up the ladder. Combination of these nano-sized dosage with poorly bioavailable drugs, unspecific target binding ability and naturally unstable curcumin further complicates the formulation aspects. Emphasis is now therefore being laid on altering natural forms of curcumin and usage of formulations like prodrug or coating of curcumin to overcome stability issues and focus more on enhancing the pharmaceutical and therapeutic ability of the nano-composites. Current studies and futuristic outlook in this direction are discussed in the review, which can serve as the basis for upcoming research which could boost commercial translational of improved nano-sized curcumin combination chemotherapy.

Analysis of drug resistance in HIV protease.

BACKGROUND: Drug resistance in HIV is the major problem limiting effective antiviral therapy. Computational techniques for predicting drug resistance profiles from genomic data can accelerate the appropriate choice of therapy. These techniques can also be used to select protease mutants for experimental studies of resistance and thereby assist in the development of next-generation therapies. RESULTS: The machine learning produced highly accurate and robust classification of HIV protease resistance. Genotype data were mapped to the enzyme structure and encoded using Delaunay triangulation. Generative machine learning models trained on one inhibitor could classify resistance from other inhibitors with varying levels of accuracy. Generally, the accuracy was best when the inhibitors were chemically similar. CONCLUSIONS: Restricted Boltzmann Machines are an effective machine learning tool for classification of genomic and structural data. They can also be used to compare resistance profiles of different protease inhibitors.

Comparative genome analysis reveals key genetic factors associated with probiotic property in Enterococcus faecium strains.

BACKGROUND: Enterococcus faecium though commensal in the human gut, few strains provide a beneficial effect to humans as probiotics while few are responsible for the nosocomial infection. Comparative genomics of E. faecium can decipher the genomic differences responsible for probiotic, pathogenic and non-pathogenic properties. In this study, we compared E. faecium strain 17OM39 with a marketed probiotic, non-pathogenic non-probiotic (NPNP) and pathogenic strains. RESULTS: E. faecium 17OM39 was found to be closely related with marketed probiotic strain T110 based on core genome analysis. Strain 17OM39 was devoid of known vancomycin, tetracycline resistance and functional virulence genes. Moreover, E. faecium 17OM39 genome was found to be more stable due to the absence of frequently found transposable elements. Genes imparting beneficial functional properties were observed to be present in marketed probiotic T110 and 17OM39 strains. Genes associated with colonization and survival within gastrointestinal tract was also detected across all the strains. CONCLUSIONS: Beyond shared genetic features; this study particularly identified genes that are responsible for imparting probiotic, non-pathogenic and pathogenic features to the strains of E. faecium. Higher genomic stability, absence of known virulence factors and antibiotic resistance genes and close genomic relatedness with marketed probiotics makes E. faecium 17OM39 a potential probiotic candidate. The work presented here demonstrates that comparative genome analyses can be applied to large numbers of genomes, to find potential probiotic candidates.

Genomic and physiological analyses of an indigenous strain, Enterococcus faecium 17OM39.

The human gut microbiome plays a crucial role in human health and efforts need to be done for cultivation and characterisation of bacteria with potential health benefits. Here, we isolated a bacterium from a healthy Indian adult faeces and investigated its potential as probiotic. The cultured bacterial strain 17OM39 was identified as Enterococcus faecium by 16S rRNA gene sequencing. The strain 17OM39 exhibited tolerance to acidic pH, showed antimicrobial activity and displayed strong cell surface traits such as hydrophobicity and autoaggregation capacity. The strain was able to tolerate bile salts and showed bile salt hydrolytic (BSH) activity, exopolysaccharide production and adherence to human HT-29 cell line. Importantly, partial haemolytic activity was detected and the strain was susceptible to the human serum. Genomics investigation of strain 17OM39 revealed the presence of diverse genes encoding for proteolytic enzymes, stress response systems and the ability to produce essential amino acids, vitamins and antimicrobial compound Bacteriocin-A. No virulence factors and plasmids were found in this genome of the strain 17OM39. Collectively, these physiological and genomic features of 17OM39 confirm the potential of this strain as a candidate probiotic.

Anthropogenic Activities Induce Depletion in Microbial Communities at Urban Sites of the River Ganges.

The Ganges is the largest river of India, worshiped by Hindus with a belief that bathing in the river causes the remission of sins and is considered very pure. It is heavily polluted by the unrestricted human usage including ritual practices, urbanization, and industrialization. Such perturbations may subsequently influence the bacterial community composition and ecosystem functioning. Here, we applied targeted amplicon sequencing to determine the impact of spatial variation on the microbial community assemblage of the Ganga River. The river bacterial community demonstrates taxonomic variability across the sites with accumulation of Firmicutes (20.9%) Verrucomicrobia (6.09%), Actinobacteria (4.51%), and Synergistetes (1.16%), at rural site while Proteobacteria (49.4%) and Bacteroidetes (12.7%) predominate at urban sites. Furthermore, sites under study establish the unique taxonomic signature which could represent the impact of spatial variation on the microbial community assemblage.

Optimization of Nutrients and Culture Conditions for Alkaline Protease Production Using Two Endophytic Micrococci: Micrococcus aloeverae and Micrococcus yunnanensis.

An endophytic species of Micrococcus was isolated from Aloe vera leaf (syn. Aloe barbadensis) and screened for protease production with five other species of Micrococcus. Data indicated that endophytic Micrococcus aloeverae AE-6 MCC 2184T and Micrococcus yunnanensis DSM 21948T showed efficient protease production potential and secreted active protease at high salt (10%), temperature (40 °C) and in wide range of pH 8-10. Unlike M. yunnanensis DSM 21948T, protease production by M. aloeverae AE-6 MCC 2184T was stringently controlled by pH. Protease induction study using different group of peptides, peptide carbohydrates and peptide macronutrient combinations showed variable response with both the organisms. Result indicated that the amount of protease was not directly related to cell biomass but it depends on nature of inducible peptides. In this study we also developed a modified agar-well assay for semi-quantitative data from large number of replicates.

Genomic and functional features of the biosurfactant producing Bacillus sp. AM13.

Genomic studies provide deeper insights into secondary metabolites produced by diverse bacterial communities, residing in various environmental niches. This study aims to understand the potential of a biosurfactant producing Bacillus sp. AM13, isolated from soil. An integrated approach of genomic and chemical analysis was employed to characterize the antibacterial lipopeptide produced by the strain AM13. Genome analysis revealed that strain AM13 harbors a nonribosomal peptide synthetase (NRPS) cluster; highly similar with known biosynthetic gene clusters from surfactin family: lichenysin (85 %) and surfactin (78 %). These findings were substantiated with supplementary experiments of oil displacement assay and surface tension measurements, confirming the biosurfactant production. Further investigation using LCMS approach exhibited similarity of the biomolecule with biosurfactants of the surfactin family. Our consolidated effort of functional genomics provided chemical as well as genetic leads for understanding the biochemical characteristics of the bioactive compound.

Interactome analyses of Salmonella pathogenicity islands reveal SicA indispensable for virulence.

BACKGROUND: Serovars of Salmonella enterica, namely Typhi and Typhimurium, reportedly, are the bacterial pathogens causing systemic infections like gastroenteritis and typhoid fever. To elucidate the role and importance in such infection, the proteins of the Type III secretion system of Salmonella pathogenicity islands and two component signal transduction systems, have been mainly focused. However, the most indispensable of these virulent ones and their hierarchical role has not yet been studied extensively. RESULTS: We have adopted a theoretical approach to build an interactome comprising the proteins from the Salmonella pathogeneicity islands (SPI) and two component signal transduction systems. This interactome was then analyzed by using network parameters like centrality and k-core measures. An initial step to capture the fingerprint of the core network resulted in a set of proteins which are involved in the process of invasion and colonization, thereby becoming more important in the process of infection. These proteins pertained to the Inv, Org, Prg, Sip, Spa, Ssa and Sse operons along with chaperone protein SicA. Amongst them, SicA was figured out to be the most indispensable protein from different network parametric analyses. Subsequently, the gene expression levels of all these theoretically identified important proteins were confirmed by microarray data analysis. Finally, we have proposed a hierarchy of the proteins involved in the total infection process. This theoretical approach is the first of its kind to figure out potential virulence determinants encoded by SPI for therapeutic targets for enteric infection. CONCLUSIONS: A set of responsible virulent proteins was identified and the expression level of their genes was validated by using independent, published microarray data. The result was a targeted set of proteins that could serve as sensitive predictors and form the foundation for a series of trials in the wet-lab setting. Understanding these regulatory and virulent proteins would provide insight into conditions which are encountered by this intracellular enteric pathogen during the course of infection. This would further contribute in identifying novel targets for antimicrobial agents.

Alishewanella solinquinati sp. nov., isolated from soil contaminated with textile dyes.

A novel Gram-negative, motile, rod-shaped, facultative anaerobic bacterial strain, KMK6(T), was isolated from soil contaminated with textile dyes from an industrial estate located at Ichalkaranji, Maharashtra, India, and its taxonomical position was established by using a polyphasic approach. The major cellular fatty acids included C17:1ω8c, summed feature 3 (C16:1ω7c and/or iso-C15:0 2-OH), C17:0, C16:0, and C18:1ω7c. The DNA G+C content of strain KMK6(T) was 48.8 mol %. 16S rRNA gene sequence analysis confirmed its placement in the genus Alishewanella, and exhibited sequence similarity levels of below 97 % to the type strains of validly published Alishewanella species. On the basis of genotypic and phenotypic evidence, strains KMK6(T) is considered to be a novel species of the genus Alishewanella, for which we propose that strain KMK6(T) (=NCIM 5295(T) =BCRC 17848(T)) is assigned to a novel species, Alishewanella solinquinati sp. nov.