Phosphate solubilizing Aspergillus Niger PH1 ameliorates growth and alleviates lead stress in maize through improved photosynthetic and antioxidant response.

Among the several threats to humanity by anthropogenic activities, contamination of the environment by heavy metals is of great concern. Upon entry into the food chain, these metals cause serious hazards to plants and other organisms including humans. Use of microbes for bioremediation of the soil and stress mitigation in plants are among the preferred strategies to provide an efficient, cost-effective, eco-friendly solution of the problem. The current investigation is an attempt in this direction where fungal strain PH1 was isolated from the rhizosphere of Parthenium hysterophorus which was identified as Aspergillus niger by sequence homology of the ITS 1 and ITS 4 regions of the rRNA. The strain was tested for its effect on growth and biochemical parameters as reflection of its potential to mitigate Pb stress in Zea mays exposed to 100, 200 and 500 µg of Pb/g of soil. In the initial screening, it was revealed that the strain has the ability to tolerate lead stress, solubilize insoluble phosphate and produce plant growth promoting hormones (IAA and SA) and other metabolites like phenolics, flavonoids, sugar, protein and lipids. Under 500 µg of Pb/g of soil, Z. mays exhibited significant growth retardation with a reduction of 31% in root length, 30.5% in shoot length, 57.5% in fresh weight and 45.2% in dry weight as compared to control plants. Inoculation of A. niger to Pb treated plants not only restored root and shoot length, rather promoted it to a level significantly higher than the control plants. Association of the strain modulated the physio-hormonal attributes of maize plants that resulted in their better growth which indicated a state of low stress. Additionally, the strain boosted the antioxidant defence system of the maize there by causing a significant reduction in the ascorbic acid peroxidase (1.5%), catalase (19%) and 1,1-diphenyl-2 picrylhydrazyl (DPPH) radical scavenging activity (33.3%), indicating a lower stress condition as compared to their non-inoculated stressed plants. Based on current evidence, this strain can potentially be used as a biofertilizer for Pb-contaminated sites where it will improve overall plant health with the hope of achieving better biological and agricultural yields.

Human Y chromosome haplogroup L1-M22 traces Neolithic expansion in West Asia and supports the Elamite and Dravidian connection.

West and South Asian populations profoundly influenced Eurasian genetic and cultural diversity. We investigate the genetic history of the Y chromosome haplogroup L1-M22, which, while prevalent in these regions, lacks in-depth study. Robust Bayesian analyses of 165 high-coverage Y chromosomes favor a West Asian origin for L1-M22 ∼20.6 thousand years ago (kya). Moreover, this haplogroup parallels the genome-wide genetic ancestry of hunter-gatherers from the Iranian Plateau and the Caucasus. We characterized two L1-M22 harboring population groups during the Early Holocene. One expanded with the West Asian Neolithic transition. The other moved to South Asia ∼8-6 kya but showed no expansion. This group likely participated in the spread of Dravidian languages. These South Asian L1-M22 lineages expanded ∼4-3 kya, coinciding with the Steppe ancestry introduction. Our findings advance the current understanding of Eurasian historical dynamics, emphasizing L1-M22's West Asian origin, associated population movements, and possible linguistic impacts.

A Comprehensive Review on Machine Learning Techniques for Protein Family Prediction.

Proteomics is a field dedicated to the analysis of proteins in cells, tissues, and organisms, aiming to gain insights into their structures, functions, and interactions. A crucial aspect within proteomics is protein family prediction, which involves identifying evolutionary relationships between proteins by examining similarities in their sequences or structures. This approach holds great potential for applications such as drug discovery and functional annotation of genomes. However, current methods for protein family prediction have certain limitations, including limited accuracy, high false positive rates, and challenges in handling large datasets. Some methods also rely on homologous sequences or protein structures, which introduce biases and restrict their applicability to specific protein families or structures. To overcome these limitations, researchers have turned to machine learning (ML) approaches that can identify connections between protein features and simplify complex high-dimensional datasets. This paper presents a comprehensive survey of articles that employ various ML techniques for predicting protein families. The primary objective is to explore and improve ML techniques specifically for protein family prediction, thus advancing future research in the field. Through qualitative and quantitative analyses of ML techniques, it is evident that multiple methods utilizing a range of classifiers have been applied for protein family prediction. However, there has been limited focus on developing novel classifiers for protein family classification, highlighting the urgent need for improved approaches in this area. By addressing these challenges, this research aims to enhance the accuracy and effectiveness of protein family prediction, ultimately facilitating advancements in proteomics and its diverse applications.

Graphylo: A deep learning approach for predicting regulatory DNA and RNA sites from whole-genome multiple alignments.

This study focuses on enhancing the prediction of regulatory functional sites in DNA and RNA sequences, a crucial aspect of gene regulation. Current methods, such as motif overrepresentation and machine learning, often lack specificity. To address this issue, the study leverages evolutionary information and introduces Graphylo, a deep-learning approach for predicting transcription factor binding sites in the human genome. Graphylo combines Convolutional Neural Networks for DNA sequences with Graph Convolutional Networks on phylogenetic trees, using information from placental mammals' genomes and evolutionary history. The research demonstrates that Graphylo consistently outperforms both single-species deep learning techniques and methods that incorporate inter-species conservation scores on a wide range of datasets. It achieves this by utilizing a species-based attention model for evolutionary insights and an integrated gradient approach for nucleotide-level model interpretability. This innovative approach offers a promising avenue for improving the accuracy of regulatory site prediction in genomics.

Bacteriophage Taxonomy: A Continually Evolving Discipline.

While taxonomy is an often underappreciated branch of science, it serves very important roles. Bacteriophage taxonomy has evolved from a discipline based mainly on morphology, characterized by the work of David Bradley and Hans-Wolfgang Ackermann, to the sequence-based approach that is taken today. The Bacterial Viruses Subcommittee of the International Committee on Taxonomy of Viruses (ICTV) takes a holistic approach to classifying prokaryote viruses by measuring overall DNA and protein similarity and phylogeny before making decisions about the taxonomic position of a new virus. The huge number of complete genomes being deposited with the National Center for Biotechnology Information (NCBI) and other public databases has resulted in a reassessment of the taxonomy of many viruses, and the future will see the introduction of new viral families and higher orders.

PanDelos-frags: A methodology for discovering pangenomic content of incomplete microbial assemblies.

Pangenomics was originally defined as the problem of comparing the composition of genes into gene families within a set of bacterial isolates belonging to the same species. The problem requires the calculation of sequence homology among such genes. When combined with metagenomics, namely for human microbiome composition analysis, gene-oriented pangenome detection becomes a promising method to decipher ecosystem functions and population-level evolution. Established computational tools are able to investigate the genetic content of isolates for which a complete genomic sequence is available. However, there is a plethora of incomplete genomes that are available on public resources, which only a few tools may analyze. Incomplete means that the process for reconstructing their genomic sequence is not complete, and only fragments of their sequence are currently available. However, the information contained in these fragments may play an essential role in the analyses. Here, we present PanDelos-frags, a computational tool which exploits and extends previous results in analyzing complete genomes. It provides a new methodology for inferring missing genetic information and thus for managing incomplete genomes. PanDelos-frags outperforms state-of-the-art approaches in reconstructing gene families in synthetic benchmarks and in a real use case of metagenomics. PanDelos-frags is publicly available at https://github.com/InfOmics/PanDelos-frags.

Mapping of conserved immunodominant epitope peptides in the outer membrane porin (Omp) L of prominent Enterobacteriaceae pathogens associated with gastrointestinal infections.

BACKGROUND: Members of Enterobacteriaceae such as Escherichia coli O 157:H7, Salmonella sp., Shigella sp., Klebsiella sp., and Citrobacter freundii are responsible for the outbreak of serious foodborne illness and other mucosal infections across the globe. The outer membrane proteins (OMPs) of Enterobacteriaceae are highly immunogenic in eliciting immune responses against pathogens. Moreover, the OMPs are highly conserved in the Enterobacteriaceae family. Sequence homology in the OMPs will ensure the presence of conserved immunodominant regions with predominant epitopes. The OmpL is such an immunogen that is highly conserved among the Enterobacteriaceae pathogens. In this study, we performed computational analysis on the outer membrane porin (Omp) L of prominent Enterobacteriaceae pathogens. RESULTS: Multiple sequence and structural alignment analysis have revealed that the OmpL protein is highly conserved among the selected Enterobacteriaceae pathogens. This amount of sequence and structural homology uncovered the conserved antibody binding B-cell epitopes in the OmpL protein. The B-cell epitopes predicted in the OmpL of Salmonella typhimurium are highly conserved among the other Enterobacteriaceae pathogens. CONCLUSION: In conclusion, these conserved B-cell epitopes will vouch for the generation of heterologous humoral immune response in conferring cross protection against the Enterobacteriaceae pathogens and control their outbreaks across the globe.

Prioritization of infectious epitopes for translational investigation in type 1 diabetes etiology.

Molecular mimicry is one mechanism by which infectious agents are thought to trigger islet autoimmunity in type 1 diabetes. With a growing number of reported infectious agents and islet antigens, strategies to prioritize the study of infectious agents are critically needed to expedite translational research into the etiology of type 1 diabetes. In this work, we developed an in-silico pipeline for assessing molecular mimicry in type 1 diabetes etiology based on sequence homology, empirical binding affinity to specific MHC molecules, and empirical potential for T-cell immunogenicity. We then assess whether potential molecular mimics were conserved across other pathogens known to infect humans. Overall, we identified 61 potentially high-impact molecular mimics showing sequence homology, strong empirical binding affinity, and empirical immunogenicity linked with specific MHC molecules. We further found that peptide sequences from 32 of these potential molecular mimics were conserved across several human pathogens. These findings facilitate translational evaluation of molecular mimicry in type 1 diabetes etiology by providing a curated and prioritized list of peptides from infectious agents for etiopathologic investigation. These results may also provide evidence for generation of infectious and HLA-specific preclinical models and inform future screening and preventative efforts in genetically susceptible populations.

Natural heteroclitic-like peptides are generated by SARS-CoV-2 mutations.

Humoral immunity is sensitive to evasion by SARS-CoV-2 mutants, but CD8 T cells seem to be more resistant to mutational inactivation. By a systematic analysis of 30 spike variant peptides containing the most relevant VOC and VOI mutations that have accumulated overtime, we show that in vaccinated and convalescent subjects, mutated epitopes can have not only a neutral or inhibitory effect on CD8 T cell recognition but can also enhance or generate de novo CD8 T cell responses. The emergence of these mutated T cell function enhancing epitopes likely reflects an epiphenomenon of SARS-CoV-2 evolution driven by antibody evasion and increased virus transmissibility. In a subset of individuals with weak and narrowly focused CD8 T cell responses selection of these heteroclitic-like epitopes may bear clinical relevance by improving antiviral protection. The functional enhancing effect of these peptides is also worth of consideration for the future development of new generation, more potent COVID-19 vaccines.

Genetic studies of heat stress regulation in goat during hot climatic condition.

Various direct and indirect environmental constraints have an impact on livestock performance. The physiological parameters, such as rectal temperature, heart rate, and respiratory rate, are the primary indicators of thermal stress. Under a stressed environment temperature humidity index (THI) had established as a vital measurement to identify the thermal stress in livestock. THI in association with climatic variations can define the environmental effect as stressful or comfortable for livestock. Goats are small ruminants that adapt to a wide range of ecological variations due to their anatomical and physiological characteristics. However, the productivity of animals declines at the individual level during thermal stress. Stress tolerance can be determined through genetic studies associated with at the cellular level using physiological as well as molecular approaches. Information on genetic association with thermal stress in goats is scanty, this severely affects their survival and hence productivity of livestock. The ever-increasing demand for food across the globe needs deciphering novel molecular markers as well as stress indicators that play a vital role in livestock improvement. This review represents an analysis of current knowledge of phenotypic differences during thermal stress and signifies the importance of physiological responses and their association at the cellular level in goats. The regulation of vital genes associated with thermal stress such as Aquaporins (AQP 0, 1, 2, 4, 5, 6, 8), aquaglyceroporins (AQP3, 7, 9, and 10) and super-aquaporins (AQP 11, 12); BAX inhibitors such as PERK (PKR like ER kinase), IRE 1(inositol-requiring-1); Redox regulating genes such as NOX; Transport of Na+ and K+ such as ATPase (ATP1A1) and several heat shock proteins have been implicated in heat-stress related adaptations have been elucidated. As these changes have a significant impact on production performance as well as on livestock productivity. Such efforts may help in the development of molecular markers and will assist the breeders to develop heat-tolerant goats with improved productivity.

Genetic variation characteristics of HA gene of influenza A virus (H3N2) in Guizhou province from 2017 to 2019 / 中国基层医药

Objective:To analyze the genetic variation characteristics of the HA gene of influenza A virus (H3N2) in Guizhou province from 2017 to 2019. Methods:Twenty strains of influenza A virus (H3N2) were randomly selected from 10 network laboratories in Guizhou province for RNA extraction. Reverse transcriptase-polymerase chain reaction and sequencing were performed. The products were analyzed using bioinformatics software.Results:The nucleotide homology of the HA gene of the 20 strains was 97.7%-100%, which was highly homologous to the vaccine strains A/Hong-Kong/4801/2014 recommended by WHO in 2017 and A/Singapore-INFIMH/16-0019/2016 recommended by WHO in 2018, but they were significantly different from the vaccine strain A/Kansas/14/2017 recommended by WHO in 2019. Genetic analysis showed that the 20 strains were divided into two branches, and the strains that were prevalent in 2019 were located in different branches, with marked genetic differences. Key site analysis showed mutations in antigenic determinants A, B, C, and E and mutations in the anterior and posterior walls of receptor binding sites. Key site analysis also showed that there was an increase in the number of glycosylation sites compared with the vaccine strains prevalent in the same year. Genetic distance, antigen sites, and glycosylation sites were slightly different between virus strains prevalent in 2017-2018 and virus strains prevalent in 2019. Conclusion:The HA gene of the influenza A virus subtype H3N2 in Guizhou province from 2017 to 2019 showed heterogeneity and gene mutation, especially in 2019. Therefore, close monitoring of the genetic evolution of the influenza A virus subtype H3N2 is necessary.

Evolutionary perspective of Big tau structure: 4a exon variants of MAPT.

The MAPT gene encoding the microtubule-associated protein tau can generate multiple isoforms by alternative splicing giving rise to proteins which are differentially expressed in specific areas of the nervous system and at different developmental stages. Tau plays important roles in modulating microtubule dynamics, axonal transport, synaptic plasticity, and DNA repair, and has also been associated with neurodegenerative diseases (tauopathies) including Alzheimer's disease and frontotemporal dementia. A unique high-molecular-weight isoform of tau, originally found to be expressed in the peripheral nervous system and projecting neurons, has been termed Big tau and has been shown to uniquely contain the large exon 4a that significantly increases the size and 3D structure of tau. With little progress since the original discovery of Big tau, more than 25 years ago, we have now completed a comprehensive comparative study to analyze the structure of the MAPT gene against available databases with respect to the composition of the tau exons as they evolved from early vertebrates to primates and human. We focused the analysis on the evolution of the 4a exon variants and their homology relative to humans. We discovered that the 4a exon defining Big tau appears to be present early in vertebrate evolution as a large insert that dramatically changed the size of the tau protein with low sequence conservation despite a stable size range of about 250aa, and in some species a larger 4a-L exon of 355aa. We suggest that 4a exon variants evolved independently in different species by an exonization process using new alternative splicing to address the growing complexities of the evolving nervous systems. Thus, the appearance of a significantly larger isoform of tau independently repeated itself multiple times during evolution, accentuating the need across vertebrate species for an elongated domain that likely endows Big tau with novel physiological functions as well as properties related to neurodegeneration.

Caenorhabditis elegans MES-3 is a highly divergent ortholog of the canonical PRC2 component SUZ12.

Polycomb Repressive Complex 2 (PRC2) catalyzes the mono-, di-, and trimethylation of histone protein H3 on lysine 27 (H3K27), which is strongly associated with transcriptionally silent chromatin. The functional core of PRC2 is highly conserved in animals and consists of four subunits. One of these, SUZ12, has not been identified in the genetic model Caenorhabditis elegans, whereas C. elegans PRC2 contains the clade-specific MES-3 protein. Through unbiased sensitive sequence similarity searches complemented by high-quality structure predictions of monomers and multimers, we here demonstrate that MES-3 is a highly divergent ortholog of SUZ12. MES-3 shares protein folds and conserved residues of key domains with SUZ12 and is predicted to interact with core PRC2 members similar to SUZ12 in human PRC2. Thus, in agreement with previous genetic and biochemical studies, we provide evidence that C. elegans contains a diverged yet evolutionary conserved core PRC2, like other animals.

First report of maize yellow mosaic virus causing maize reddening in Henan,China.

A novel polerovirus maize yellow mosaic virus (MaYMV) has been discovered in Asia (Chen et al. 2016; Lim et al. 2018; Sun et al. 2019; Wang et al. 2016), East Africa (Guadie et al. 2018; Massawe et al. 2018) and South America (Gonçalves et al. 2017). MaMYV was first reported to infect maize (Zea mays L.) showing yellow mosaic symptoms on the leaves in Yunnan, Guizhou, and yellowing and dwarfing symptoms on the leaves in Anhui provinces of China in 2016 (Chen et al. 2016; Wang et al. 2016). An East African isolate of MaYMV has recently been shown to induce leaf reddening in several maize genotypes (Stewart et al. 2020). To our knowledge the leaf reddening symptoms in maize was not reported in China and MaYMV was not reported in Henan province, China. A survey of viral diseases on maize was carried out during the autumn of 2021 in Zhengzhou (Henan province), China. During the survey, the leaves showing reddening symptoms were observed on maize plants in all four fields investigated. Symptomatic leaves of 12 plants from four fields of Xingyang county, Zhengzhou (n=12) were collected and mixed for metatranscriptomics sequencing, and total RNA was extracted and subjected to an rRNA removal procedure using a Ribo-zero Magnetic kit according to the manufacturer's instructions (Epicentre, an Illumina® company). cDNA libraries were constructed using a TruSeq™ RNA sample prep kit (Illumina). Barcoded libraries were paired-end sequenced on an Illumina HiSeq X ten platform at Shanghai Biotechnology Co., Ltd. (Shanghai, China) according to the manufacturer's instructions (www.illumina.com). In total 67607392 clean reads were de novo assembled using CLC Genomics Workbench (version:6.0.4). 105796 contigs were obtained. The assembled contigs were queried by homology search tools (BLASTn and BLASTx) against public database(GenBank). One 5,457 nucleotide (nt) long contig with the most reads of 558826 was obtained and blast analysis showed it shared 99.3% nt sequence identity (99% coverage) with MaYMV Yunnan4 isolate (KU291100).. According to the sequencing data no other plant viruses except MaYMV were present in the sequencing data. To confirm the presence of this virus, twelve leaf samples showing reddening symptoms were detected by RT-PCR using specific primer pairs for CP full length open reading frame (F: ATGAATACGGGAGGTAGAAA, R: CTATTTCGGGTTTTGAACAT). Amplicons with expected size of 594 bp were gained in seven samples and three of them were cloned into pMD18T vector and sequenced. The three isolates (OM417795, OM417796, and OM417797) shared 99.16% to 99.83% nt sequence identity with MaYMV-Yunnan3 isolate (KU291100). Further P0 sequence analysis of the three samples (OM417798, OM417799, and OM417800) with primer pairs F: ATGGGGGGAGTGCCTAAAGC/R: TCATAACTGATGGAATTCCC showed they shared 99.5% to 99.62% nt sequence identity with MaYMV-Yunnan3 isolate.To our knowledge, this is the first report of the occurrence of MaYMV infecting maize in Henan, China. Besides, our finding firstly discovered reddening symptoms caused by MaYMV on maize in China which is different from the previous symptoms observed in the other three provinces of China possibly due to the different maize varieties grown in different areas. According to our investigation, maize showing reddening symptoms was common in the fields. Henan province is the main corn production area in China. Corn leaf aphid (Rhopalosiphum maidis), the insect vector of MaYMV, is an important pest of corn in Henan province, thereby the occurrence of MaYMV might cause potential threat to maize production in China.

EnsembleFam: towards more accurate protein family prediction in the twilight zone.

BACKGROUND: Current protein family modeling methods like profile Hidden Markov Model (pHMM), k-mer based methods, and deep learning-based methods do not provide very accurate protein function prediction for proteins in the twilight zone, due to low sequence similarity to reference proteins with known functions. RESULTS: We present a novel method EnsembleFam, aiming at better function prediction for proteins in the twilight zone. EnsembleFam extracts the core characteristics of a protein family using similarity and dissimilarity features calculated from sequence homology relations. EnsembleFam trains three separate Support Vector Machine (SVM) classifiers for each family using these features, and an ensemble prediction is made to classify novel proteins into these families. Extensive experiments are conducted using the Clusters of Orthologous Groups (COG) dataset and G Protein-Coupled Receptor (GPCR) dataset. EnsembleFam not only outperforms state-of-the-art methods on the overall dataset but also provides a much more accurate prediction for twilight zone proteins. CONCLUSIONS: EnsembleFam, a machine learning method to model protein families, can be used to better identify members with very low sequence homology. Using EnsembleFam protein functions can be predicted  using just sequence information with better accuracy than state-of-the-art methods.

GERONIMO: A tool for systematic retrieval of structural RNAs in a broad evolutionary context.

BACKGROUND: While web-based tools such as BLAST have made identifying conserved gene homologs appear easy, genes with variable sequences pose significant challenges. Functionally important noncoding RNAs (ncRNA) often show low sequence conservation due to genetic variations, including insertions and deletions. Rather than conserved sequences, these RNAs possess highly conserved structural features across a broad phylogenetic range. Such features can be identified using the covariance models approach, which combines sequence alignment with a secondary RNA structure consensus. However, running standard implementation of that approach (Infernal) requires advanced bioinformatics knowledge compared to user-friendly web services like BLAST. The issue is partially addressed by RNAcentral, which can be used to search for homologs across a broad range of ncRNA sequence collections from diverse organisms but not across the genome assemblies. RESULTS: Here, we present GERONIMO, which conducts evolutionary searches across hundreds of genomes in a fully automated way. It provides results extended with taxonomy context, as summary tables and visualizations, to facilitate analysis for user convenience. Additionally, GERONIMO supplements homologous sequences with genomic regions to analyze promoter motifs or gene collinearity, enhancing the validation of results. CONCLUSION: GERONIMO, built using Snakemake, has undergone extensive testing on hundreds of genomes, establishing itself as a valuable tool in the identification of ncRNA homologs across diverse taxonomic groups. Consequently, GERONIMO facilitates the investigation of the evolutionary patterns of functionally significant ncRNA players, whose understanding has previously been limited to individual organisms and close relatives.

Leveraging homologies for cross-species plasma proteomics in ungulates using data-independent acquisition.

The collection of blood plasma is minimally invasive, and the fluid is a rich source of proteins for biomarker studies in both humans and animals. Plasma protein analysis by mass spectrometry (MS) can be challenging, though modern data acquisition strategies, such as sequential window acquisition of all theoretical fragment ion spectra (SWATH), enable reproducible quantitation of hundreds of proteins in non-depleted plasma from humans and laboratory model animals. Although there is strong potential to enhance veterinary and translational research, SWATH-based plasma proteomics in non-laboratory animals is virtually non-existent. One limitation to date is the lack of comprehensively annotated genomes to aid protein identification. The current study established plasma peptide spectral repositories for sheep and cattle that enabled quantification of over 200 proteins in non-depleted plasma using SWATH approach. Moreover, bioinformatics pipeline was developed to leverage inter-species homologies to enhance the depth of baseline libraries and plasma protein quantification in bovids. Finally, the practical utility of using bovid libraries for SWATH data extraction in taxonomically related non-domestic ungulate species (giraffe) has been demonstrated. SIGNIFICANCE: Ability to quickly generate comprehensive spectral libraries is limiting the applicability of data-independent acquisition, such as SWATH, to study proteomes of non-laboratory animals. We describe an approach to obtain relatively shallow foundational plasma repositories from domestic ruminants and employ homology searches to increase the depth of data, which we subsequently extend to unsequenced ungulates using SWATH method. When applied to cross-species proteomics, the number of proteins quantified by our approach far exceeds what is traditionally used in plasma protein tests.

Rapid Identification of Secondary Structure and Binding Site Residues in an Intrinsically Disordered Protein Segment.

Mycobacterium tuberculosis harbours nine toxin-antitoxin (TA) systems of the MazEF family. MazEF TA modules are of immense importance due to the perceived role of the MazF toxin in M. tuberculosis persistence and disease. The MazE antitoxin has a disordered C-terminal domain that binds the toxin, MazF and neutralizes its endoribonuclease activity. However, the structure of most MazEF TA complexes remains unsolved till date, obscuring structural and functional information about the antitoxins. We present a facile method to identify toxin binding residues on the disordered antitoxin. Charged residue scanning mutagenesis was used to screen a yeast surface displayed MazE6 antitoxin library against its purified cognate partner, the MazF6 toxin. Binding residues were deciphered by probing the relative reduction in binding to the ligand by flow cytometry. We have used this to identify putative antitoxin interface residues and local structure attained by the antitoxin upon interaction in the MazEF6 TA system and the same methodology is readily applicable to other intrinsically disordered protein regions.

Occurrence and risk factors of nontuberculous mycobacteria in tuberculosis-suspected patients in the north of Iran.

BACKGROUND AND OBJECTIVES: Some Nontuberculous Mycobacteria (NTM) can occasionally infect the human population and cause infections having symptoms similar to tuberculosis (TB). This study tried to provide updated data about the frequency and diversity of NTM species. MATERIALS AND METHODS: Suspicious samples of Mycobacterium tuberculosis (MTB) with both positive results in Ziehl-Neelsen (ZN) staining and Löwenstein-Jensen medium culturing were evaluated during January 2016 and December 2018 in Gorgan, Iran. After determination of MTB isolates by the growth rate, pigmentation status, the niacin test, and the insertion sequence 6110 (IS6110) PCR assay, other unknown isolates (presumably NTM) were detected by the 16S rDNA sequencing method and drawing the phylogenetic tree. Based on the patients' demographic information, their risk factors were also assessed. RESULTS: Among 226 culture-positive samples, obtained from 2994 individuals with suspected symptoms of TB, the analyses found 12 (5.3%) NTM and three Mycobacterium caprae isolates. Mycobacterium simiae (6/12) was the most prevalent NTM species. The average nucleotide similarity value was 98.2% ± 3.7. In comparison to patients with MTB (211 confirmed cases), other mycobacterium infections were more common in patients over 65 years old (Odd ratio (95% convenience interval): 2.96 (0.69 - 12.59), P = 0.14). CONCLUSION: Although the NTM species has a small portion in TB suspected patients, their prevalence has increased, mainly in elderly patients. Moreover, M. simiae was the most prevalent NTM species in our region. Therefore, identification of common species in each region is recommended and clinicians should pay more attention to them in each region.

Mapping B-Cell Epitopes for Nonspecific Lipid Transfer Proteins of Legumes Consumed in India and Identification of Critical Residues Responsible for IgE Binding.

Nonspecific lipid transfer proteins (nsLTPs) have been categorized as panallergens and display widespread occurrence across plant-kingdom. Present study, investigated B-cell epitopes for LTPs from chickpea, mung-bean, cowpea, pigeon-pea, and soybean via in silico methods. In-silico predicted regions were evaluated for epitope-conservancy and property-based peptide similarity search by different allergen databases. Additionally, the in-silico predicted regions were compared with the experimentally validated epitopes of peach-LTP. Sequence-homology studies showed that chickpea and mung-bean LTPs shared significant homology, i.e., >70% and >60%, respectively, with other LTP allergens from lentil, garden-pea, peanut, etc. Phylogenetic-analysis also showed chickpea and mung-bean LTPs to be closely related to allergenic LTPs from lentil and peanut, respectively. Epitope-conservation analysis showed that two of the predicted B-cell epitopic regions in chickpea and mung-bean LTPs were also conserved in other allergenic LTPs from peach, peanut, garden-pea, lentil, and green-bean, and might serve as conserved B-cell epitopes of the LTP protein family. Property-distance index values for chickpea and mung-bean LTPs also showed that most of the epitopes shared similarity with the reported allergens like-lentil, peanut, apple, plum, tomato, etc. Present findings, may be explored for identification of probable allergenicity of novel LTPs, on the basis of the reported conserved B-cell epitopes, responsible for potential cross-reactivity.