Dynamic shock wave driven simultaneous crystallographic and molecular switching between α-Fe2O3 and Fe3O4 nanoparticles - a new finding.

Switchable nanostructured materials with a low-cost and fast processing have diverse practical applications in the modern electronic industries, but such materials are highly scarce. Hence, there is a great demand for identifying the externally stimulated solid-state switchable phase transition materials for several industrial applications. In this paper, we present the experimentally observed solid-state molecular level switchable phase transitions of nanocrystalline iron oxide materials: {α-Fe2O3 (R-3c) to Fe3O4 (Fd-3m) and Fe3O4 (Fd-3m) to α-Fe2O3 (R-3c)} under dynamic shock wave loaded conditions, and the results were evaluated by diffraction, and vibrational and optical spectroscopic techniques. To date, this is most probably the first report which demonstrates the simultaneous molecular and crystallographic switchable-phase-transitions enforced by dynamic shock waves such that the title material is proposed for sensors and molecular switching applications.

Importance of wastewater-based epidemiology for detecting and monitoring SARS-CoV-2.

Coronavirus disease caused by the SARS-CoV-2 virus has emerged as a global challenge in terms of health and disease monitoring. COVID-19 infection is mainly spread through the SARS-CoV-2 infection leading to the development of mild to severe clinical manifestations. The virus binds to its cognate receptor ACE2 which is widely expressed among different tissues in the body. Notably, SARS-CoV-2 shedding in the fecal samples has been reported through the screening of sewage water across various countries. Wastewater screening for the presence of SARS-CoV-2 provides an alternative method to monitor infection threat, variant identification, and clinical evaluation to restrict the virus progression. Multiple cohort studies have reported the application of wastewater treatment approaches and epidemiological significance in terms of virus monitoring. Thus, the manuscript outlines consolidated and systematic information regarding the application of wastewater-based epidemiology in terms of monitoring and managing a viral disease outbreak like COVID-19.

Insights from the molecular docking aided interaction analysis of HfQ with small RNAs.

Hfq, RNA binding protein, is widely found in most of the prokaryotes. It plays a key role in gene regulation by binding with small RNA and facilitates mRNA pairing there by suppress or boost translation according to RNA structures. Interaction between sRNAs and HfQ in Salmonella SL1344 were screened using Co-Immuno Precipitation (HfQ-CoIP) studies earlier. We have formulated an In silico approach, to model the 3D structures of 155 sRNA and studied their interactions with HfQ proteins. We have reported the key interacting PHE42, LEU7, VAL27, PHE39 and PRO21 residues of HfQ binds with many small RNAs. Further mutation of PHE42 in to ALA42 in HfQ leads to loss of sRNA binding efficiency. We have differentiated the interactions in to HfQ binding and non-binding sRNAs, based on Atomic Contact Energy and area. This methodology may be applied generically for functional grouping of small RNAs in any organism.

Genetic diversity and evolutionary dynamics of dengue isolates from India.

Dengue virus (DENV) is the mosquito borne virus which causes Dengue Haemorrhagic Fever and Dengue Shock Syndrome. It consists of four distinct serotypes (DENV 1-4). DENV 1, 3 and 4 were classified into five genotypes (GI-GV), where as DENV-2 belongs to American and Cosmopolitan genotypes. Dengue virus is most prevalent in south and Southeast Asia including India. This study was initiated to study the genetic diversity and evolution among the Dengue isolates in India. Pairwise comparison of amino acid sequences among the serotypes has shown that DENV-3 is having less sequence diversity compared to other serotypes having differences in their amino acid numbers. We have analyzed the 50 Indian strains and 19 of those strains have been identified as recombinant strains by using RDP4 package, which are then excluded for future selection. Episodic positive selection of DENV was obtained using MEME with P value is ≤ 5. Positive selection on several codons was used to correlate the genetic diversity between serotypes. This study clearly established that diversity of amino acids and inter genotypic recombination of strains are the major cause for antigenicity variation and evolution of DENV within India.

Transcriptome based Identification of silver stress responsive sRNAs from Bacillus cereus ATCC14579.

Microbes modulate their metabolic and physiological mechanisms in response to changing environmental conditions. It is our interest to identify small regulatory RNAs using microarray expression data (GSE26043) obtained from B. cereus ATCC 14579 in AgNO3 stress. By definition, expression of transcripts from the Intergenic Regions (IGR) with >=2 fold under silver stress is predicted as novel small RNAs. Computational analysis of the IGR expression levels extracted from the available microarray data help in the identification of stress responsive sRNAs with rare promoters (Sigma 24, 28, 32, 54 and 70) followed by terminator signals predicted using the sRNAscanner tool. We predicted 1512 sRNA specific regions on both positive and negative strands collectively. Thus, a non-redundant high scoring unique 860 sRNAs with distinct promoter (S24: 83, S28: 86, S32: 31, S54: 57, S70: 223, sRNA_specific_S70: 380) and terminator signals are reported. These unique computationally predicted sRNA regions were verified with the highly expressing IGRs from the microarray data. It should be noted that 14 sRNAs reported in earlier studies were also found in this dataset. This study has reported 71 additional sRNAs from the transcriptome under metal stress response. Hence, we use global transcriptomics data for the identification of novel sRNAs in B. cereus. We described a general model using a procedure for the identification of small regulatory RNAs using microarray expression data with appropriate cross validation modules. It is found that some sRNAs reported in this study were found to have multiple rare promoters. This opens the possibility of sRNA activation under multiple stress condition. These sRNA data reported in this study should be characterized for their mRNA targets and molecular functional networks in future investigations.

PanGeT: Pan-genomics tool.

A decade after the concept of Pan-genome was first introduced; research in this field has spread its tentacles to areas such as pathogenesis of diseases, bacterial evolutionary studies and drug resistance. Gene content-based differentiation of virulent and a virulent strains of bacteria and identification of pathogen specific genes is imperative to understand their physiology and gain insights into the mechanism of genome evolution. Subsequently, this will aid in identifying diagnostic targets and in developing and selecting vaccines. The root of pan-genomic studies, however, is to identify the core genes, dispensable genes and strain specific genes across the genomes belonging to a clade. To this end, we have developed a tool, "PanGeT - Pan-genomics Tool" to compute the 'pan-genome' based on comparisons at the genome as well as the proteome levels. This automated tool is implemented using LaTeX libraries for effective visualization of overall pan-genome through graphical plots. Links to retrieve sequence information and functional annotations have also been provided. PanGeT can be downloaded from http://pranag.physics.iisc.ernet.in/PanGeT/ or https://github.com/PanGeTv1/PanGeT.

Draft Genome Sequence of Paracoccus sp. MKU1, a New Bacterial Strain Isolated from an Industrial Effluent with Potential for Bioremediation.

Paracoccus sp. MKU1, a novel dimethylformamide degrading bacterial strain was originally isolated from an industrial effluent, Tirupur region, Tamil Nadu, India. Here, we report the draft genome sequence of Paracoccus sp. MKU1, which could provide the genetic insights on its evolution and application of this versatile bacterium for effective degradation of xenobiotics and thus in bioremediation.

BrucellaBase: Genome information resource.

Brucella sp. causes a major zoonotic disease, brucellosis. Brucella belongs to the family Brucellaceae under the order Rhizobiales of Alphaproteobacteria. We present BrucellaBase, a web-based platform, providing features of a genome database together with unique analysis tools. We have developed a web version of the multilocus sequence typing (MLST) (Whatmore et al., 2007) and phylogenetic analysis of Brucella spp. BrucellaBase currently contains genome data of 510 Brucella strains along with the user interfaces for BLAST, VFDB, CARD, pairwise genome alignment and MLST typing. Availability of these tools will enable the researchers interested in Brucella to get meaningful information from Brucella genome sequences. BrucellaBase will regularly be updated with new genome sequences, new features along with improvements in genome annotations. BrucellaBase is available online at http://www.dbtbrucellosis.in/brucellabase.html or http://59.99.226.203/brucellabase/homepage.html.

Omics of Brucella: Species-Specific sRNA-Mediated Gene Ontology Regulatory Networks Identified by Computational Biology.

Brucella is an intracellular bacterium that causes the zoonotic infectious disease, brucellosis. Brucella species are currently intensively studied with a view to developing novel global health diagnostics and therapeutics. In this context, small RNAs (sRNAs) are one of the emerging topical areas; they play significant roles in regulating gene expression and cellular processes in bacteria. In the present study, we forecast sRNAs in three Brucella species that infect humans, namely Brucella melitensis, Brucella abortus, and Brucella suis, using a computational biology analysis. We combined two bioinformatic algorithms, SIPHT and sRNAscanner. In B. melitensis 16M, 21 sRNA candidates were identified, of which 14 were novel. Similarly, 14 sRNAs were identified in B. abortus, of which four were novel. In B. suis, 16 sRNAs were identified, and five of them were novel. TargetRNA2 software predicted the putative target genes that could be regulated by the identified sRNAs. The identified mRNA targets are involved in carbohydrate, amino acid, lipid, nucleotide, and coenzyme metabolism and transport, energy production and conversion, replication, recombination, repair, and transcription. Additionally, the Gene Ontology (GO) network analysis revealed the species-specific, sRNA-based regulatory networks in B. melitensis, B. abortus, and B. suis. Taken together, although sRNAs are veritable modulators of gene expression in prokaryotes, there are few reports on the significance of sRNAs in Brucella. This report begins to address this literature gap by offering a series of initial observations based on computational biology to pave the way for future experimental analysis of sRNAs and their targets to explain the complex pathogenesis of Brucella.

Computational prediction of secretion systems and secretomes of Brucella: identification of novel type IV effectors and their interaction with the host.

Brucella spp. are facultative intracellular pathogens that cause brucellosis in various mammals including humans. Brucella survive inside the host cells by forming vacuoles and subverting host defence systems. This study was aimed to predict the secretion systems and the secretomes of Brucella spp. from 39 complete genome sequences available in the databases. Furthermore, an attempt was made to identify the type IV secretion effectors and their interactions with host proteins. We predicted the secretion systems of Brucella by the KEGG pathway and SecReT4. Brucella secretomes and type IV effectors (T4SEs) were predicted through genome-wide screening using JVirGel and S4TE, respectively. Protein-protein interactions of Brucella T4SEs with their hosts were analyzed by HPIDB 2.0. Genes coding for Sec and Tat pathways of secretion and type I (T1SS), type IV (T4SS) and type V (T5SS) secretion systems were identified and they are conserved in all the species of Brucella. In addition to the well-known VirB operon coding for the type IV secretion system (T4SS), we have identified the presence of additional genes showing homology with T4SS of other organisms. On the whole, 10.26 to 14.94% of total proteomes were found to be either secreted (secretome) or membrane associated (membrane proteome). Approximately, 1.7 to 3.0% of total proteomes were identified as type IV secretion effectors (T4SEs). Prediction of protein-protein interactions showed 29 and 36 host-pathogen specific interactions between Bos taurus (cattle)-B. abortus and Ovis aries (sheep)-B. melitensis, respectively. Functional characterization of the predicted T4SEs and their interactions with their respective hosts may reveal the secrets of host specificity of Brucella.

Identification of Recombination and Positively Selected Genes in Brucella.

Brucella is a facultative intracellular bacterium belongs to the class alpha proteobacteria. It causes zoonotic disease brucellosis to wide range of animals. Brucella species are highly conserved in nucleotide level. Here, we employed a comparative genomics approach to examine the role of homologous recombination and positive selection in the evolution of Brucella. For the analysis, we have selected 19 complete genomes from 8 species of Brucella. Among the 1599 core genome predicted, 24 genes were showing signals of recombination but no significant breakpoint was found. The analysis revealed that recombination events are less frequent and the impact of recombination occurred is negligible on the evolution of Brucella. This leads to the view that Brucella is clonally evolved. On other hand, 56 genes (3.5 % of core genome) were showing signals of positive selection. Results suggest that natural selection plays an important role in the evolution of Brucella. Some of the genes that are responsible for the pathogenesis of Brucella were found positively selected, presumably due to their role in avoidance of the host immune system.

Draft Genome Sequence of Brucella abortus Virulent Strain 544.

Here, we present the draft genome sequence and annotation of Brucella abortus virulent strain 544. The genome of this strain is 3,289,405 bp long, with 57.2% G+C content. A total of 3,259 protein-coding genes and 60 RNA genes were predicted.

Draft Genome Sequence of Brucella abortus S99: Designated Antigenic Smooth Reference Strain Used in Diagnostic Tests in India.

Brucella abortus strain S99 is widely used for the preparation of colored, plain, recombinant and smooth lipopolysaccharide antigens for the preparation of Brucella diagnostic kits. The genome of this strain was sequenced and the length of the genome was 3,253,175 bp, with 57.2% G+C content. A total of 3,365 protein coding genes and 53 RNA genes were predicted.

Phylogenetic reconstruction of endophytic fungal isolates using internal transcribed spacer 2 (ITS2) region.

Endophytic fungi are inhabitants of plants, living most part of their lifecycle asymptomatically which mainly confer protection and ecological advantages to the host plant. In this present study, 48 endophytic fungi were isolated from the leaves of three medicinal plants and characterized based on ITS2 sequence - secondary structure analysis. ITS2 secondary structures were elucidated with minimum free energy method (MFOLD version 3.1) and consensus structure of each genus was generated by 4SALE. ProfDistS was used to generate ITS2 sequence structure based phylogenetic tree respectively. Our elucidated isolates were belonging to Ascomycetes family, representing 5 orders and 6 genera. Colletotrichum/Glomerella spp., Diaporthae/Phomopsis spp., and Alternaria spp., were predominantly observed while Cochliobolus sp., Cladosporium sp., and Emericella sp., were represented by singletons. The constructed phylogenetic tree has well resolved monophyletic groups with >50% bootstrap value support. Secondary structures based fungal systematics improves not only the stability; it also increases the precision of phylogenetic inference. Above ITS2 based phylogenetic analysis was performed for our 48 isolates along with sequences of known ex-types taken from GenBank which confirms the efficiency of the proposed method. Further, we propose it as superlative marker for reconstructing phylogenetic relationships at different taxonomic levels due to their lesser length.

Draft Genome Sequence of Brucella melitensis Strain ADMAS-G1, Isolated from Placental Fluids of an Aborted Goat.

Here, we report the draft genome sequence and annotation of the Brucella melitensis strain designated ADMAS-G1, isolated from placental fluids of an aborted goat. The length of the genome is 3,284,982 bp, with a 57.3% GC content. A total of 3,325 protein-coding genes and 63 RNA genes were predicted.

Computational small RNA prediction in bacteria.

Bacterial, small RNAs were once regarded as potent regulators of gene expression and are now being considered as essential for their diversified roles. Many small RNAs are now reported to have a wide array of regulatory functions, ranging from environmental sensing to pathogenesis. Traditionally, noncoding transcripts were rarely detected by means of genetic screens. However, the availability of approximately 2200 prokaryotic genome sequences in public databases facilitates the efficient computational search of those molecules, followed by experimental validation. In principle, the following four major computational methods were applied for the prediction of sRNA locations from bacterial genome sequences: (1) comparative genomics, (2) secondary structure and thermodynamic stability, (3) 'Orphan' transcriptional signals and (4) ab initio methods regardless of sequence or structure similarity; most of these tools were applied to locate the putative genomic sRNA locations followed by experimental validation of those transcripts. Therefore, computational screening has simplified the sRNA identification process in bacteria. In this review, a plethora of small RNA prediction methods and tools that have been reported in the past decade are discussed comprehensively and assessed based on their attributes, compatibility, and their prediction accuracy.

Comparative genomics reveals 'novel' Fur regulated sRNAs and coding genes in diverse proteobacteria.

Ferric uptake regulator (Fur) is a transcriptional regulator controlling the expression of genes involved in iron homeostasis and plays an important role in pathogenesis. Fur-regulated sRNAs/CDSs were found to have upstream Fur Binding Sites (FBS). We have constructed a Positional Weight Matrix from 100 known FBS (19 nt) and tracked the 'Orphan' FBSs. Possible Fur regulated sRNAs and CDSs were identified by comparing their genomic locations with the 'Orphan' FBSs identified. Thirty-eight 'novel' and all known Fur regulated sRNAs in nine proteobacteria were identified. In addition, we identified high scoring FBSs in the promoter regions of the 304 CDSs and 68 of them were involved in siderophore biosynthesis, iron-transporters, two-component system, starch/sugar metabolism, sulphur/methane metabolism, etc. The present study shows that the Fur regulator controls the expression of genes involved in diverse metabolic activities and it is not limited to iron metabolism alone.

Modeling and structural analysis of cellulases using Clostridium thermocellum as template.

Cellulase is one of the most widely distributed enzymes with wide application. They are involved in conversion of biomass into simpler sugars. Cellulase of Trichoderma longibrachiatum, a known cellulolytic fungus was compared with Clostridium thermocellum [AAA23226.1] cellulase. Blastp was performed with AAA23226.1 as query sequence to obtain nine similar sequences from NCBI protein data bank. The physicochemical properties of cellulase were analyzed using ExPASy's ProtParam tool namely ProtParam, SOPMA and GOR IV. Homology modeling was done using SWISS MODEL and checked quality by RMSD values using VMD1.9.1. Active sites of each model were predicted using automated active site prediction server of SCFBio. Study revealed instability of cellulase of two eukaryotic strains namely Trichoderma longibrachiatum [CAA43059.1] and Melanocarpus albomyces [CAD56665.1]. The negative GRAVY score value of cellulases ensured better interaction and activity in aqueous phase. It was found that molecular weight (M. Wt) ranges between 25-127.56 kDa. Iso-electric point (pI) of cellulases was found to be acidic in nature. GOR IV and SOPMA were used to predict secondary structure of cellulase, which showed that random coil, was dominated. Neighbor joining tree with C. thermocellum [AAA23226.1] cellulase as root showed that cellulases of Thermoaerobacter subterraneus [ZP_07835928] and C. thermocellum [CAA4305.1] were more similar to eukaryotic cellulases supported by least boot strap values. Pseudoalteromonas haloplanktis cellulase was found to be the ideal model supported by least RMSD score among the predicted structures. Trichoderma longibrachiatum cellulase was found to be the best compared to other cellulases, which possess high number of active sites with ASN and THR rich active sites. CYS residues were also present ensuring stable interaction and better bonding. Hydrophilic residues were found high in active sites of all analyzed models and template.

Junker: an intergenic explorer for bacterial genomes.

In the past few decades, scientists from all over the world have taken a keen interest in novel functional units such as small regulatory RNAs, small open reading frames, pseudogenes, transposons, integrase binding attB/attP sites, repeat elements within the bacterial intergenic regions (IGRs) and in the analysis of those "junk" regions for genomic complexity. Here we have developed a web server, named Junker, to facilitate the in-depth analysis of IGRs for examining their length distribution, four-quadrant plots, GC percentage and repeat details. Upon selection of a particular bacterial genome, the physical genome map is displayed as a multiple loci with options to view any loci of interest in detail. In addition, an IGR statistics module has been created and implemented in the web server to analyze the length distribution of the IGRs and to understand the disordered grouping of IGRs across the genome by generating the four-quadrant plots. The proposed web server is freely available at the URL http://pranag.physics.iisc.ernet.in/junker/.

Global transcriptome analysis of Bacillus cereus ATCC 14579 in response to silver nitrate stress.

Silver nanoparticles (AgNPs) were synthesized using Bacillus cereus strains. Earlier, we had synthesized monodispersive crystalline silver nanoparticles using B. cereus PGN1 and ATCC14579 strains. These strains have showed high level of resistance to silver nitrate (1 mM) but their global transcriptomic response has not been studied earlier. In this study, we investigated the cellular and metabolic response of B. cereus ATCC14579 treated with 1 mM silver nitrate for 30 & 60 min. Global expression profiling using genomic DNA microarray indicated that 10% (n = 524) of the total genes (n = 5234) represented on the microarray were up-regulated in the cells treated with silver nitrate. The majority of genes encoding for chaperones (GroEL), nutrient transporters, DNA replication, membrane proteins, etc. were up-regulated. A substantial number of the genes encoding chemotaxis and flagellar proteins were observed to be down-regulated. Motility assay of the silver nitrate treated cells revealed reduction in their chemotactic activity compared to the control cells. In addition, 14 distinct transcripts overexpressed from the 'empty' intergenic regions were also identified and proposed as stress-responsive non-coding small RNAs.