The zinc-finger protein Z4 cooperates with condensin II to regulate somatic chromosome pairing and 3D chromatin organization.

Chromosome pairing constitutes an important level of genome organization, yet the mechanisms that regulate pairing in somatic cells and the impact on 3D chromatin organization are still poorly understood. Here, we address these questions in Drosophila, an organism with robust somatic pairing. In Drosophila, pairing preferentially occurs at loci consisting of numerous architectural protein binding sites (APBSs), suggesting a role of architectural proteins (APs) in pairing regulation. Amongst these, the anti-pairing function of the condensin II subunit CAP-H2 is well established. However, the factors that regulate CAP-H2 localization and action at APBSs remain largely unknown. Here, we identify two factors that control CAP-H2 occupancy at APBSs and, therefore, regulate pairing. We show that Z4, interacts with CAP-H2 and is required for its localization at APBSs. We also show that hyperosmotic cellular stress induces fast and reversible unpairing in a Z4/CAP-H2 dependent manner. Moreover, by combining the opposite effects of Z4 depletion and osmostress, we show that pairing correlates with the strength of intrachromosomal 3D interactions, such as active (A) compartment interactions, intragenic gene-loops, and polycomb (Pc)-mediated chromatin loops. Altogether, our results reveal new players in CAP-H2-mediated pairing regulation and the intimate interplay between inter-chromosomal and intra-chromosomal 3D interactions.

Culture-Independent Workflow for Nanopore MinION-Based Sequencing of Influenza A Virus.

Whole-genome sequencing (WGS) of influenza A virus (IAV) is crucial for identifying diverse subtypes and newly evolved variants and for selecting vaccine strains. In developing countries, where facilities are often inadequate, WGS is challenging to perform using conventional next-generation sequencers. In this study, we established a culture-independent, high-throughput native barcode amplicon sequencing workflow that can sequence all influenza subtypes directly from a clinical specimen. All segments of IAV in 19 clinical specimens, irrespective of their subtypes, were amplified simultaneously using a two-step reverse transcriptase PCR (RT-PCR) system. First, the library was prepared using the ligation sequencing kit, barcoded individually using the native barcodes, and sequenced on the MinION MK 1C platform with real-time base-calling. Then, subsequent data analyses were performed with the appropriate tools. WGS of 19 IAV-positive clinical samples was carried out successfully with 100% coverage and 3,975-fold mean coverage for all segments. This easy-to-install and low-cost capacity-building protocol took only 24 h complete from extracting RNA to obtaining finished sequences. Overall, we developed a high-throughput portable sequencing workflow ideal for resource-limited clinical settings, aiding in real-time surveillance, outbreak investigation, and the detection of emerging viruses and genetic reassortment events. However, further evaluation is required to compare its accuracy with other high-throughput sequencing technologies to validate the widespread application of these findings, including WGS from environmental samples. IMPORTANCE The Nanopore MinION-based influenza sequencing approach we are proposing makes it possible to sequence the influenza A virus, irrespective of its diverse serotypes, directly from clinical and environmental swab samples, so that we are not limited to virus culture. This third-generation, portable, multiplexing, and real-time sequencing strategy is highly convenient for local sequencing, particularly in low- and middle-income countries like Bangladesh. Furthermore, the cost-efficient sequencing method could provide new opportunities to respond to the early phase of an influenza pandemic and enable the timely detection of the emerging subtypes in clinical samples. Here, we meticulously described the entire process that might help the researcher who will follow this methodology in the future. Our findings suggest that this proposed method is ideal for clinical and academic settings and will aid in real-time surveillance and in the detection of potential outbreak agents and newly evolved viruses.

An Immunoinformatics Prediction of Novel Multi-Epitope Vaccines Candidate Against Surface Antigens of Nipah Virus.

Nipah virus (NiV) is an emerging zoonotic virus causing outbreaks of encephalitis and respiratory illnesses in humans, with high mortality. NiV is considered endemic in Bangladesh and Southeast Asia. There are no licensed vaccines against NiV. This study aimed at predicting a dual-antigen multi-epitope subunit chimeric vaccine against surface-glycoproteins G and F of NiV. Targeted proteins were subjected to immunoinformatics analyses to predict antigenic B-cell and T-cell epitopes. The proposed vaccine designs were implemented based on the conservancy, population coverage, molecular docking, immune simulations, codon adaptation, secondary mRNA structure, and in-silico cloning. Total 40 T and B-cell epitopes were found to be conserved, antigenic (vaxijen-value > 0.4), non-toxic, non-allergenic, and human non-homologous. Of 12 hypothetical vaccines, two (NiV_BGD_V1 and NiV_BGD_V2) were strongly immunogenic, non-allergenic, and structurally stable. The proposed vaccine candidates show a negative Z-score (- 6.32 and - 6.67) and 83.6% and 89.3% of most rama-favored regions. The molecular docking confirmed the highest affinity of NiV_BGD_V1 and NiV_BGD_V2 with TLR-4 (ΔG = - 30.7) and TLR8 (ΔG = - 20.6), respectively. The vaccine constructs demonstrated increased levels of immunoglobulins and cytokines in humans and could be expressed properly using an adenoviral-based pAdTrack-CMV expression vector. However, more experimental investigations and clinical trials are needed to validate its efficacy and safety. Supplementary Information: The online version contains supplementary material available at 10.1007/s10989-022-10431-z.

Microbiome signature and diversity regulates the level of energy production under anaerobic condition.

The microbiome of the anaerobic digester (AD) regulates the level of energy production. To assess the microbiome diversity and composition in different stages of anaerobic digestion, we collected 16 samples from the AD of cow dung (CD) origin. The samples were categorized into four groups (Group-I, Group-II, Group-III and Group-IV) based on the level of energy production (CH4%), and sequenced through whole metagenome sequencing (WMS). Group-I (n = 2) belonged to initial time of energy production whereas Group-II (n = 5), Group-III (n = 5), and Group-IV (n = 4) had 21-34%, 47-58% and 71-74% of CH4, respectively. The physicochemical analysis revealed that level of energy production (CH4%) had significant positive correlation with digester pH (r = 0.92, p < 0.001), O2 level (%) (r = 0.54, p < 0.05), and environmental temperature (°C) (r = 0.57, p < 0.05). The WMS data mapped to 2800 distinct bacterial, archaeal and viral genomes through PathoScope (PS) and MG-RAST (MR) analyses. We detected 768, 1421, 1819 and 1774 bacterial strains in Group-I, Group-II, Group-III and Group-IV, respectively through PS analysis which were represented by Firmicutes, Bacteroidetes, Proteobacteria, Actinobacteria, Spirochaetes and Fibrobacteres phyla (> 93.0% of the total abundances). Simultaneously, 343 archaeal strains were detected, of which 95.90% strains shared across four metagenomes. We identified 43 dominant species including 31 bacterial and 12 archaeal species in AD microbiomes, of which only archaea showed positive correlation with digester pH, CH4 concentration, pressure and temperature (Spearman correlation; r > 0.6, p < 0.01). The indicator species analysis showed that the species Methanosarcina vacuolate, Dehalococcoides mccartyi, Methanosarcina sp. Kolksee and Methanosarcina barkeri were highly specific for energy production. The correlation network analysis showed that different strains of Euryarcheota and Firmicutes phyla exhibited significant correlation (p = 0.021, Kruskal-Wallis test; with a cutoff of 1.0) with the highest level (74.1%) of energy production (Group-IV). In addition, top CH4 producing microbiomes showed increased genomic functional activities related to one carbon and biotin metabolism, oxidative stress, proteolytic pathways, membrane-type-1-matrix-metalloproteinase (MT1-MMP) pericellular network, acetyl-CoA production, motility and chemotaxis. Importantly, the physicochemical properties of the AD including pH, CH4 concentration (%), pressure, temperature and environmental temperature were found to be positively correlated with these genomic functional potentials and distribution of ARGs and metal resistance pathways (Spearman correlation; r > 0.5, p < 0.01). This study reveals distinct changes in composition and diversity of the AD microbiomes including different indicator species, and their genomic features that are highly specific for energy production.

Comprehensive annotations of the mutational spectra of SARS-CoV-2 spike protein: a fast and accurate pipeline.

Infecting millions of people, the SARS-CoV-2 is evolving at an unprecedented rate, demanding advanced and specified analytic pipeline to capture the mutational spectra. In order to explore mutations and deletions in the spike (S) protein - the most-discussed protein of SARS-CoV-2 - we comprehensively analyzed 35,750 complete S protein-coding sequences through a custom Python-based pipeline. This GISAID-collected dataset of until 24 June 2020 covered six continents and five major climate zones. We identified 27,801 (77.77% sequences) mutated strains compared to reference Wuhan-Hu-1 wherein 84.40% of these strains mutated by only a single amino acid (aa). An outlier strain (EPI_ISL_463893) from Bosnia and Herzegovina possessed six aa substitutions. We also identified 11 residues with high aa mutation frequency, and each contains four types of aa variations. The infamous D614G variant has spread worldwide with ever-rising dominance and across regions with different climatic conditions alongside L5F and D936Y mutants, which have been documented throughout all regions and climate zones, respectively. We also found 988 unique aa substitutions spanned across 660 residues, which differed significantly among different continents (p = .003) and climatic zones (p = .021) as inferred with the Kruskal-Wallis test. Besides, 17 in-frame deletions at four sites adjacent to receptor-binding-domain were determined that may have a possible impact on attenuation. This study provides a fast and accurate pipeline for identifying mutations and deletions from the large dataset for coding and also non-coding sequences as evidenced by the representative analysis on existing S protein data. By using separate multi-sequence alignment, removing ambiguous sequences and in-frame stop codons, and utilizing pairwise alignment, this method can derive both synonymous and non-synonymous mutations (strain_ID reference aa:mutation position:strain aa). We suggest that the pipeline will aid in the evolutionary surveillance of any SARS-CoV-2 encoded proteins and will prove to be crucial in tracking the ever-increasing variation of many other divergent RNA viruses in the future. The code is available at https://github.com/SShaminur/Mutation-Analysis.