Self-organizing maps: a tool to ascertain taxonomic relatedness based on features derived from 16S rDNA sequence

Intestinal Microbiota Reduction Followed by Fasting Discloses Microbial Triggering of Inflammation in Rheumatoid Arthritis

Rheumatoid arthritis (RA) synovitis is dominated by monocytes/macrophages with inflammatory patterns resembling microbial stimulation. In search of triggers, we reduced the intestinal microbiome in 20 RA patients (open label study DRKS00014097) by bowel cleansing and 7-day fasting (≤250 kcal/day) and performed immune monitoring and microbiome sequencing. Patients with metabolic syndrome (n = 10) served as a non-inflammatory control group. Scores of disease activity (DAS28/SDAI) declined within a few days and were improved in 19 of 20 RA patients after breaking the fast (median ∆DAS28 = -1.23; ∆SDAI = -43%) or even achieved remission (DAS28 < 2.6/n = 6; SDAI < 3.3/n = 3). Cytometric profiling with 46 different surface markers revealed the most pronounced phenomenon in RA to be an initially increased monocyte turnover, which improved within a few days after microbiota reduction and fasting. Serum levels of IL-6 and zonulin, an indicator of mucosal barrier disruption, decreased significantly. Endogenous cortisol levels increased during fasting but were insufficient to explain the marked improvement. Sequencing of the intestinal microbiota indicated that fasting reduced potentially arthritogenic bacteria and changed the microbial composition to species with broader metabolic capabilities. More eukaryotic, predominantly fungal colonizers were observed in RA, suggesting possible involvement. This study demonstrates a direct link between the intestinal microbiota and RA-specific inflammation that could be etiologically relevant and would support targeted nutritional interventions against gut dysbiosis as a causal therapeutic approach.

Phylogenomic analysis of Citrobacter sp. strain AAK_AS5 and its metabolic capabilities to support nitrogen removal behavior

Despite the ubiquity of the genus Citrobacter in clinical, industrial, and environmental scenarios, a large number of Citrobacter strains have not been explored at the genome-scale level. In this study, accurate taxonomic assignment of strain AAK_AS5 isolated from activated sludge was achieved by in-silico genomic comparison using Overall Genome-based Relatedness Indices (ANI(OAT): 97.55%, ANIb:97.28%, and ANIm: 97.83%) that indicated its closest identity to the related strain Citrobacter portucalensis A60^T . Results were consistent with a digital DNA-DNA hybridization value of 80% with C. portucalensis A60^T which was greater than the species boundary value >70% for delineating closely related bacterial species. Gene mining through Kyoto Encyclopedia of Genes and Genomes (KEGG), and annotation using rapid annotation subsystem technology (RAST) revealed the notable gene contents for nitrogen metabolism and other pathways associated with nitrate/nitrite ammonification (28 genes), ammonia assimilation (22 genes), and denitrification pathways (14 genes). Furthermore, the strain AAK_AS5 also exhibited a high soluble chemical oxygen demand (sCOD), NH₄ ⁺ -N, and NO₃ ^- -N removal efficiency of 91.4%, 90%, and 93.6%, respectively thus validating its genetic capability for utilizing both (NH₄ )₂ SO₄ and KNO₃ as the nitrogen source. The study provided deeper insights into the phylogenomics and the genetic potential of Citrobacter, sp. strain AAK AS5 associated with nitrogen metabolism thus signifying the potential application of the isolate for treating nitrogen-rich wastewaters.

Mapping Microbial Capacities for Bioremediation: Genes to Genomics

Bioremediation is a process wherein the decontamination strategies are designed so that a site could achieve the environmental abiotic and biotic parameters close to its baseline. In the process, the driving force is the available microbial genetic degradative capabilities, which are supported by required nutrients so that the desired expression of these capabilities could be exploited in favour of removal of pollutants. With genomics tools not only the available abilities could be estimated but their dynamic performance could also be established. These tools are now playing important role in bioprocess optimization, which not only derive the bio-stimulation plans but also could suggest possible genetic bio-augmentation options.

The Identification of Discriminating Patterns from 16S rRNA Gene to Generate Signature for Bacillus Genus

The 16S ribosomal RNA (16S rRNA) gene has been widely used for the taxonomic classification of bacteria. A molecular signature is a set of nucleotide patterns, which constitute a regular expression that is specific to each particular taxon. Our main goal was to identify discriminating nucleotide patterns in 16S rRNA gene and then to generate signatures for taxonomic classification. To demonstrate our approach, we used the phylum Firmicutes as a model using representative taxa Bacilli (class), Bacillales (order), Bacillaceae (family), and Bacillus (genus), according to their dominance at each hierarchical taxonomic level. We applied combined composite vector and multiple sequence alignment approaches to generate gene-specific signatures. Further, we mapped all the patterns into the different hypervariable regions of 16S rRNA gene and confirmed the most appropriate distinguishing region as V3-V4 for targeted taxa. We also examined the evolution in discriminating patterns of signatures across taxonomic levels. We assessed the comparative classification accuracy of signatures with other methods (i.e., RDP Classifier, KNN, and SINA). Results revealed that the signatures for taxa Bacilli, Bacillales, Bacillaceae, and Bacillus could correctly classify isolate sequences with sensitivity of 0.99, 0.97, 0.94, and 0.89, respectively, and specificity close to 0.99. We developed signature-based software DNA Barcode Identification (DNA BarID) for taxonomic classification that is available at website http://www.neeri.res.in/DNA_BarID.htm . This pattern-based study provides a deeper understanding of taxon-specific discriminating patterns in 16S rRNA gene with respect to taxonomic classification.

Visualized analysis of cellular fatty acid profiles of Vibrio parahaemolyticus strains under cold stress

Vibrio parahaemolyticus is a common foodborne bacterial pathogen, which survives in cold environments and is sometimes difficult to culture. Fatty acid analysis under cold stress was conducted for several V. parahaemolyticus strains using gas chromatography/mass spectrometry, and the results were compared with those of the controls. All the fatty acid profiles obtained were visualized by multidimensional scaling (MDS) and self-organized map (SOM). It was observed that the fatty acid profiles of V. parahaemolyticus substantially changed under cold stress. The percentage of methyl palmitate remarkably decreased and that of methyl palmitoleate (except for two strains) and methyl oleate increased. These findings demonstrate the role of fatty acids in cold stress. The changes in the fatty acid profiles illustrated by MDS and SOM could differentiate strains under cold stress from the controls and can potentially lead to a method of detecting injured cold-stressed V. parahaemolyticus.

Integrated perspective for effective bioremediation

Identification of factors which can influence the natural attenuation process with available microbial genetic capacities can support the bioremediation which has been viewed as the safest procedure to combat with anthropogenic compounds in ecosystems. With the advent of molecular techniques, assimilatory capacity of an ecosystem can be defined with changing community dynamics, and if required, the essential genetic potential can be met through bioaugmentation. At the same time, intensification of microbial processes with nutrient balancing, expressing and enhancing the degradative capacities, could reduce the time frame of restoration of the ecosystem. The new concept of ecosystems biology has added greatly to conceptualize the networking of the evolving microbiota of the niche that helps in effective application of bioremediation tools to manage pollutants as additional carbon source.