Multiple Sequence Research Articles

Unveiling the Complexity of cis-Regulation Mechanisms in Kinases: A Comprehensive Analysis.

Protein cis-regulatory elements (CREs) are regions that modulate the activity of a protein through intramolecular interactions. Kinases, pivotal enzymes in numerous biological processes, often undergo regulatory control via inhibitory interactions in cis. This study delves into the mechanisms of cis regulation in kinases mediated by CREs, employing a combined structural and sequence analysis. To accomplish this, we curated an extensive dataset of kinases featuring annotated CREs, organized into homolog families through multiple sequence alignments. Key molecular attributes, including disorder and secondary structure content, active and ATP-binding sites, post-translational modifications, and disease-associated mutations, were systematically mapped onto all sequences. Additionally, we explored the potential for conformational changes between active and inactive states. Finally, we explored the presence of these kinases within membraneless organelles and elucidated their functional roles therein. CREs display a continuum of structures, ranging from short disordered stretches to fully folded domains. The adaptability demonstrated by CREs in achieving the common goal of kinase inhibition spans from direct autoinhibitory interaction with the active site within the kinase domain, to CREs binding to an alternative site, inducing allosteric regulation revealing distinct types of inhibitory mechanisms, which we exemplify by archetypical representative systems. While this study provides a systematic approach to comprehend kinase CREs, further experimental investigations are imperative to unravel the complexity within distinct kinase families. The insights gleaned from this research lay the foundation for future studies aiming to decipher the molecular basis of kinase dysregulation, and explore potential therapeutic interventions.

Characterisation of Three Ovine KRTAP13 Family Genes and Their Association with Wool Traits in Chinese Tan Sheep.

Understanding the genetic basis of wool traits is crucial for improving wool production. In this study, we investigated the ovine KAP13 gene family, which in humans contains multiple members, while only one member has been identified to date in sheep. Three ovine KRTAP13 genes, likely representing KRTAP13-1, KRTAP13-2, and KRTAP13-4, were identified through sequence analysis and phylogenetic comparisons. These genes are positioned on chromosome 1, between KRTAP15-1 and KRTAP27-1, in a pattern that is like the arrangement in humans but not identical. Analyses revealed multiple sequence variants of each gene in 356 sheep from a variety of wool, meat, and dual-purpose breeds. The effect of these genes on four fibre traits: mean fibre curvature (MFC), mean fibre diameter (MFD), coefficient of variation of fibre diameter (CVFD), and fibre diameter standard deviation (FDSD), was assessed in 240 lambs of the Chinese Tan sheep breed. An allele of KRTAP13-2 was revealed to be associated with a decrease in FDSD and CVFD in heterotypic fibres. No associations were found between KRTAP13-4 variation and wool traits, and an association analysis for KRTAP13-1 was not conducted because no variation was found in this gene in the Chinese Tan sheep studied. These findings suggest a potential role for KRTAP13-2 in regulating wool traits, particularly fibre diameter uniformity in larger heterotypic hair fibres, and suggest its potential use as a marker for improving wool traits.

Identification of a 301 bp promoter core region of the SrUGT91D2 gene from Stevia rebaudiana that contributes to hormone and abiotic stress inducibility

BackgroundThe UDP-glucuronosyltransferase 91D2 (SrUGT91D2) gene is a crucial element in the biosynthetic pathway of steviol glycosides (SGs) and is responsible for creating 1,2-β-D glucosidic bonds at the C19 and C13 positions. This process plays a vital role in the synthesis of rebaudioside M (RM) and rebaudioside D (RD). The promoter, which regulates gene expression, requires functional analysis to understand gene expression regulation. However, investigations into the function of the promoter of SrUGT91D2 (pSrUGT91D2) have not been reported.ResultsThe pSrUGT91D2 was isolated from six S. rebaudiana lines, and subsequent multiple sequence comparisons revealed the presence of a 26 bp inDel fragment (pSrUGT91D2-B1188 type) in lines GP, GX, 110, 1114, and B1188 but not in the pSrUGT91D2 of line 023 (pSrUGT91D2-023 type). Bioinformatics analysis revealed a prevalence of significant cis-regulatory elements (CREs) within the promoter sequences, including those responsive to abscisic acid, light, anaerobic conditions, auxin, drought, low temperature, and MeJA. To verify the activity of pSrUGT91D2, the full-length promoter and a series of 5’ deletion fragments (P1–P7) and a 3’ deletion fragment (P8) from various lines were fused with the reporter β-glucuronidase (GUS) gene to construct the plant expression vector, pCAMBIA1300-pro∷GUS. The transcriptional activity of these genes was examined in tobacco leaves through transient transformation. GUS tissue staining analysis and enzyme activity assays demonstrated that both the full-length promoter and truncated pSrUGT91D2 were capable of initiating GUS expression in tobacco leaves. Interestingly, P8-pSrUGT91D2-B1188 (containing the inDel segment, 301 bp) exhibited enhanced activity in driving GUS gene expression. Transient expression studies of P8-pSrUGT91D2-B1188 and P8-pSrUGT91D2-023 in response to exogenous hormones (abscisic acid and indole-3-acetic acid) and light indicated the necessity of the inDel region for P8 to exhibit transcriptional activity, as it displayed strong responsiveness to abscisic acid (ABA), indole-3-acetic acid (IAA), and light induction.ConclusionsThese findings contribute to a deeper understanding of the regulatory mechanism of the upstream region of the SrUGT91D2 gene and provide a theoretical basis for future studies on the interaction between CREs of pSrUGT91D2 and related transcription factors.

Double sequences of complex uncertain variables associated with multiplier sequences

Abstract In this article we introduce the notion of double sequences of complex uncertain variables associated with multiplier sequences. We study their different algebraic and topological properties like solidity, symmetricity, completeness etc.

An Operations Chain Model for Automatic Assessment of Operation Procedure for Equipment Operators

Automatic assessment of the operation ability of operators based on computers is an essential approach for improving the effectiveness of equipment operation training and enhancing equipment safety. Present methods primarily focus on the operation results but pay less attention to the operation procedure. One reason is that there is a lack of a model that has the ability to describe all probable paths to accomplish the same task. Therefore, an operations chain model is put forward for the first time to describe the standard operation procedure and relationships among operations based on the decomposition of operational tasks and the relationships among the various operations required to fulfill the task. A specific operation task corresponds to an operations chain, which will form one or multiple standard operation sequences that will allow trainees to complete the same task through different paths. The Needleman–Wunsch sequence alignment algorithm is introduced to match the trainees’ operation sequence with all standard sequences. The maximum alignment result is the score of the trainees’ operations. An example shows that the operations chain model can accurately describe the complex structure of the standard operating procedures. The Needleman–Wunsch sequence alignment algorithm can objectively evaluate the trainee’s operation capabilities. The combination of the operations chain model and sequence alignment algorithm can form a complete operation procedure assessment method that is friendlier to trainees and has more objective evaluation results. The method will help to improve the effectiveness of the competency assessment of equipment operators.

SNRPB2 in the pan-cancer landscape: A bioinformatics exploration and validation in hepatocellular carcinoma

Aberrant splicing is a significant contributor to gene expression abnormalities in cancer. SNRPB2, a component of U2 small nuclear ribonucleoprotein particles (snRNPs), contributes to the assembly of the spliceosome, the molecular machinery responsible for splicing. To date, few studies have investigated the role of SNRPB2 in tumorigenesis. We examined data sourced from various public databases, such as The Cancer Genome Atlas(TCGA), the Clinical Proteomic Tumor Analysis Consortium(CPTAC), and Gene Expression Omnibus(GEO). Our investigation included gene expression, genomic and epigenomic scrutiny, gene set enrichment assessment(GSEA), and immune cell infiltration evaluation. Furthermore, we performed empirical validation to ascertain the impact of SNRPB2 suppression on the proliferation and migration of liver cancer cells. Analysis of gene expression revealed widespread upregulation of SNRPB2 across a spectrum of cancer types, with heightened levels of SNRPB2 expression in numerous tumors linked to unfavorable prognosis. Genomic and epigenomic assessments revealed connections between SNRPB2 expression and variations in SNRPB2 copy number, DNA methylation patterns, and RNA modifications. Through gene set enrichment analysis, the involvement of SNRPB2 in vital biological processes and pathways related to cancer was identified. Furthermore, scrutiny of immune cell infiltration suggested a potential relationship between SNRPB2 and the tumor microenvironment, which was reinforced by multiple single-cell sequencing profiles. Subsequent experimental validation revealed that silencing SNRPB2 effectively impeded the proliferation and migration of liver cancer cells. Taken together, these findings underscore the prospective utility of SNRPB2 as a prognostic biomarker and a promising candidate for immunotherapy in cancer. It is necessary to engage in additional exploration into its underlying mechanisms and clinical treatment potential.

Multi-site DNA methylation alterations of peripheral blood mononuclear cells serve as novel biomarkers for the diagnosis of AIS/stage I lung adenocarcinoma: A multi-center cohort study.

Early diagnosis remains an obstacle for improving the outcome of lung adenocarcinoma (LUAD). DNA methylation changes in peripheral blood mononuclear cells (PBMCs) could reflect immune response to tumorigenesis, providing the theoretical basis for early cancer diagnosis based on immune cell profiling. This multi-center study evaluated the DNA methylation patterns based on PBMCs samples from 1115 individuals at nine medical centers. Genome-wide DNA methylation profiling of PBMCs in a discovery cohort (35 LUAD patients and 50 healthy controls) was performed using Illumina 850K microarray. Candidate differentially methylated CpG positions (DMPs) were selected and validated in a two-step DMPs screening cohort (65 LUAD patients and 80 healthy controls) by pyrosequencing and multiple target region methylation enrichment sequencing (MTRMES). Then, an early LUAD Diagnostic Panel (LDP score) based on multi-site methylation-specific chip-based digital PCR was constructed in a training set and then confirmed in a validation set from the LDP score development cohort (389 AIS/stage I LUAD patients and 293 healthy controls). Besides, we included 157 other cancer patients, including 52 gastric cancer (GC) patients, 50 breast cancer (BC) patients, and 55 colorectal cancer (CRC) patients to assess the specificity of LDP score. In addition, we also evaluated the early warning ability of LDP score for LUAD in a prospective cohort (46 people who were at high-risk of developing LC). A total of 1415 LUAD-specific DMPs were identified. Then, six DMPs were selected for validation and three DMPs were finally verified. The LDP score was constructed by combining the three DMPs, age, and gender, and showed an AUC of 0.916, sensitivity of 88.17%, and specificity of 80.20% in combined set, outperforming traditional methods, such as CEA and CT (detection rate: 87.79% vs. 4.69%; 87.79% vs. 35.21%). This diagnostic performance was confirmed in sub-types of LUAD with clinical challenges, such as 6-20mm LUAD (AUC: 0.914, 95%CI: 0.889-0.934) and ground-glass nodules (AUC: 0.916, 95%CI: 0.889-0.938). Importantly, our LDP score had significant improvement in terms of selecting high-risk individuals who should receive low-dose computed tomography (87.80% vs. 9.28%). Remarkably, LDP score could predict LUAD around two years before clinical diagnosis in our prospective cohort. The novel developed LDP score represented a convenient and effective assay for the detection of AIS/stage I LUAD with high sensitivity and specificity, and had demonstrated unique advantages over traditional detection methods.

Analysis of the deformation of conical shells made by 4D Printing of composites

4D printing of composites (4DPC) is a technique that allows the manufacturing of composite structures to shape without the use of a complex-shaped mold. Instead, only a flat mold is utilized. This innovative technique has been employed to make composite leaf springs with performance comparable to metallic springs, omega stiffeners, and corrugated core for flexible wings. Recently, this technique was applied to fabricate composite conical shells. While experimental work has successfully demonstrated the transformation from flat to conical shape, the development of a numerical method to replicate this transformation is highly desirable. The availability of such method not only provides theoretical support for the experimental result, it also provides means to develop other shapes. The lay-up sequence for transforming flat to conical shapes involves curvilinear fibers. Most if not all finite elements currently available deal only with straight fibers (even though the boundaries of the element may be curved). The objective of this research is to examine the efficiency of the analysis for the deformation of composite from flat to curve made by 4DPC by special finite elements containing curved fibers. The developed finite elements were used to determine the shapes of conical shells made using multiple distinct lay-up sequences. The direction of bending in curvilinear fiber structures is significantly influenced by the orientation of the fibers. This highlights the critical role of fiber orientation and layer composition in achieving desired shapes in 4D printed composites.

An integrative single-cell atlas for exploring the cellular and temporal specificity of genes related to neurological disorders during human brain development

Single-cell technologies have enhanced comprehensive knowledge regarding the human brain by facilitating an extensive transcriptomic census across diverse brain regions. Nevertheless, understanding the cellular and temporal specificity of neurological disorders remains ambiguous due to developmental variations. To address this gap, we illustrated the dynamics of disorder risk gene expression under development by integrating multiple single-cell RNA sequencing datasets. We constructed a comprehensive single-cell atlas of the developing human brain, encompassing 393,060 single cells across diverse developmental stages. Temporal analysis revealed the distinct expression patterns of disorder risk genes, including those associated with autism, highlighting their temporal regulation in different neuronal and glial lineages. We identified distinct neuronal lineages that diverged across developmental stages, each exhibiting temporal-specific expression patterns of disorder-related genes. Lineages of nonneuronal cells determined by molecular profiles also showed temporal-specific expression, indicating a link between cellular maturation and the risk of disorder. Furthermore, we explored the regulatory mechanisms involved in early brain development, revealing enriched patterns of fetal cell types associated with neuronal disorders indicative of the prenatal stage’s influence on disease determination. Our findings facilitate unbiased comparisons of cell type‒disorder associations and provide insight into dynamic alterations in risk genes during development, paving the way for a deeper understanding of neurological disorders.

Investigation into the Acceptability of Moderate-to-Large Volume Subcutaneous Injections in Healthy Volunteers: Results from a Single-Center Randomized Controlled Study.

Therapeutic proteins are often delivered by subcutaneous (SC) autoinjector to enable self-administration. Autoinjectors typically deliver up to 1 mL injected volumes per dose. Delivery of larger volumes may be limited by injection site discomfort, including pain, swelling, and redness. Delivery at a slower rate may mitigate this discomfort. This single-center, randomized, crossover study evaluated the acceptability and tolerability of varying volumes and delivery rates of SC saline in healthy volunteers. Eligible participants were adults (18-65 years) with a body mass index of 18.5-32.0 kg/m2. Participants (N = 24) were randomized to multiple sequences of infusions over five visits, with infusions ranging from 1 to 5 mL at rates of 1.50-6.00 mL/minute (min) and including a 1 mL SC infusion in 10seconds (s) at a rate of 6.00 mL/min. The primary objective was to identify acceptable volume and delivery rates of SC saline, as assessed by visual analogue scale (VAS) pain scores, a tolerability and acceptability questionnaire, and infusion leakage. Infusions that met the acceptability criteria were 1 mL in 10s, 4 mL in 58s, and 3 mL in 2mins. Higher delivery volumes and rates were associated with higher VAS pain scores but remained within the VAS acceptability criteria. These findings may support the development of larger-volume injectors for self-administration of future medicines.

Computational Analysis and Inhibition Study of Carbonic Anhydrase from Azadirachta indica Leaves

Introduction: Carbonic anhydrase (CA) has been an enzyme of great interest for its application in carbon dioxide sequestration. A total of 66 protein sequences of plant CAs were computationally analyzed and submitted to bioinformatics for motif and domain identification, multiple sequence alignment, and phylogenetic analysis. Method: The current work aims to extend knowledge among researchers in better understanding the structure of AZDI CA by analyzing its physicochemical properties, secondary structure prediction, 3D modeling of protein sequence, and its validation using a variety of conventional computational methods. Results: The accuracy of the predicted 3D structure checked by the Ramachandran plot generated by PROCHECK showed that for the CA protein sequence 93.1%, was observed in the most favored regions, VERIFY 3D 69.44% and ERRAT 98.09%. AZDI CA was docked with various anions and sulphonamide derivatives to study their inhibitory effect and calculate binding energy by using Autodock 4.2. Ethoxzolamide is found to be a better inhibitor of AZDI CA with binding energy -8.71 kCal/mol and KI value 0.0004 mM. Further MD simulation of the docked complex of ethoxzolamide with AZDI CA was done using SCHRODINGER DESMOND software. Conclusion: The outcomes of this research will have a significant influence on biochemistry, biotechnology, and potential applications of AZDI CA and similar plant CAs in determining potent inhibitors for drug targets in treating various diseases.

Outbreak of SARS-CoV-2 variants in Iraqi Kurdistan region.

Coronavirus disease 2019 (COVID-19) first appeared in Iraq, including the Iraqi Kurdistan region governorates, in March 2020. 48,494 samples were collected from public hospitals in the Kurdish governates from February 2021 to May 2022. Viral RNA was extracted, and real time quantitative polymerase chain reaction (RT-PCR) was used to detect the COVID-19 variants. Statistical analysis of patients' clinical data was performed. The RT-PCR results identified the Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron (B.1.1.529) variants in the Kurdistan governorates. Young adults (20-39 years) had significantly higher rate of infection than children (1-11 months) and older adults (80-89 years). The Delta wave was more contiguous, spread more easily, and more fatal than the Alpha and Omicron waves. The highest number of COVID-19 cases was reported in Sulaymaniyah and Duhok; and the highest death rate was reported in Sulaymaniyah. The death rate in males was higher than in females, especially among older people. Fatigue, cough, and fever were common symptoms among the three variants. The phylogenetic tree revealed that the L-type of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) was a descendant of the S-type at an early stage of evolution. The L-type could spread faster in Kurdistan. Multiple sequence alignment (MSA) confirmed that all L-type variants in different countries were 100% similar in sequence, and all were mutated in the regions 8782: ORF1ab and 28144: ORF8 703. This study described the COVID-19 waves, pathogenesis, and evolution of the virus in the Iraqi Kurdistan region.

GenRCA: a user-friendly rare codon analysis tool for comprehensive evaluation of codon usage preferences based on coding sequences in genomes

BackgroundThe study of codon usage bias is important for understanding gene expression, evolution and gene design, providing critical insights into the molecular processes that govern the function and regulation of genes. Codon Usage Bias (CUB) indices are valuable metrics for understanding codon usage patterns across different organisms without extensive experiments. Considering that there is no one-fits-all index for all species, a comprehensive platform supporting the calculation and analysis of multiple CUB indices for codon optimization is greatly needed.ResultsHere, we release GenRCA, an updated version of our previous Rare Codon Analysis Tool, as a free and user-friendly website for all-inclusive evaluation of codon usage preferences of coding sequences. In this study, we manually reviewed and implemented up to 31 codon preference indices, with 65 expression host organisms covered and batch processing of multiple gene sequences supported, aiming to improve the user experience and provide more comprehensive and efficient analysis.ConclusionsOur website fills a gap in the availability of comprehensive tools for species-specific CUB calculations, enabling researchers to thoroughly assess the protein expression level based on a comprehensive list of 31 indices and further guide the codon optimization.

Epidemiology, genetic characterization and population structure analysis of lumpy skin disease virus from North India.

Lumpy skin disease (LSD) is a transboundary, viral disease of cattle with a significant economic impact on the livestock industry. This study describes the epidemiological investigations of outbreaks of LSD that occurred in 2022 in three Indian states viz., Haryana, Himachal Pradesh and Rajasthan and the genetic characterization of Lumpy skin disease viruses (LSDVs). Also, the population structure analysis of LSDVs was carried out. Out of 138 scab samples tested from suspected cattle for LSDV, 106 were found positive. Of these, nine representative scab samples were further genetically characterized. Phylogenetic analysis based on the P32 and EEV gene sequences depicted that the LSDV strains of the present study had nucleotide identity of 100% and 99.10-99.45%, respectively with the LSDV/2019 field strains of India. Multiple sequence alignment of the EEV glycoprotein gene sequences revealed nucleotide polymorphisms at three positions viz., G178A, G253A and A459G in circulating LSDV/2022 field strains. Based on the median joining network analysis of the EEV gene, 12 haplotypes were identified among the LSDV populations. Population structure analysis corresponding to the EEV gene revealed high haplotype (0.8486 ± 0.026) and low nucleotide diversities (0.00636 ± 0.0006) and negative values for neutrality indices, indicating a high number of closely related haplotypes and the studied population may have undergone a recent expansion. The findings will help in understanding the distribution and dynamics of LSDV populations, which will prove pivotal in designing and implementing effective management and control strategies.

DiscovEpi: automated whole proteome MHC-I-epitope prediction and visualization

BackgroundAntigen presentation is a central step in initiating and shaping the adaptive immune response. To activate CD8+ T cells, pathogen-derived peptides are presented on the cell surface of antigen-presenting cells bound to major histocompatibility complex (MHC) class I molecules. CD8+ T cells that recognize these complexes with their T cell receptor are activated and ideally eliminate infected cells. Prediction of putative peptides binding to MHC class I (MHC-I) is crucial for understanding pathogen recognition in specific immune responses and for supporting drug and vaccine design. There are reliable databases for epitope prediction algorithms available however they primarily focus on the prediction of epitopes in single immunogenic proteins.ResultsWe have developed the tool DiscovEpi to establish an interface between whole proteomes and epitope prediction. The tool allows the automated identification of all potential MHC-I-binding peptides within a proteome and calculates the epitope density and average binding score for every protein, a protein-centric approach. DiscovEpi provides a convenient interface between automated multiple sequence extraction by organism and cell compartment from the database UniProt for subsequent epitope prediction via NetMHCpan. Furthermore, it allows ranking of proteins by their predicted immunogenicity on the one hand and comparison of different proteomes on the other. By applying the tool, we predict a higher immunogenic potential of membrane-associated proteins of SARS-CoV-2 compared to those of influenza A based on the presented metrics epitope density and binding score. This could be confirmed visually by comparing the epitope maps of the influenza A strain and SARS-CoV-2.ConclusionAutomated prediction of whole proteomes and the subsequent visualization of the location of putative epitopes on sequence-level facilitate the search for putative immunogenic proteins or protein regions and support the study of adaptive immune responses and vaccine design.

Genome mining of Bacillus thuringiensis strain SY49.1 reveals novel candidate pesticidal and bioactive compounds.

Bacillus thuringiensis SY49.1 (Bt SY49.1) strain has promising insecticidal and fungicidal activity against phytopathogens and pests. Therefore, we selected this strain for whole-genome sequencing (WGS), annotation and analysis, with the aim of identifying genes responsible for producing putative pesticidal toxins, antimicrobial metabolites and plant growth-promoting features. Our results showed that the SY49.1 genome is 6. 32 Mbp long with a GC content of 34.68%. Genome mining revealed the presence of multiple gene inventories for the biosynthesis of bioactive compounds such as insecticidal delta endotoxins, secondary metabolites, and several plant growth-promoting proteins. Multiple sequence alignment revealed residue variations in the toxic core of Cry1Ab when compared with known Cry1Ab sequences from Bt nomenclature databases. This suggests that the cry1Ab of SY49.1 is a new kind of its group. Among the predicted secondary metabolites, we found a kurstakin with a predicted peptide that differs from the known kurstakin peptide available in the NORINE database. In addition, lipopeptides extracted from SY49.1 suppressed the growth of Verticillium dahliae and Fusarium oxysporum. We anticipate that the complete genome of Bt SY49.1 may provide a model for properly understanding and studying antimicrobial compound mining, genetic diversity among the B. cereus group, and pathogenicity against insects. This is the first report on the WGS and mining of the Bt strain isolated from Turkey. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Diversity, Distribution and Structural Prediction of the Pathogenic Bacterial Effectors EspN and EspS.

Many Gram-negative enterobacteria translocate virulence proteins (effectors) into intestinal epithelial cells using a type III secretion system (T3SS) to subvert the activity of various cell functions possess. Many T3SS effectors have been extensively characterized, but there are still some effector proteins whose functional information is completely unknown. In this study, two predicted effectors of unknown function, EspN and EspS (Escherichia coli secreted protein N and S), were selected for analysis of translocation, distribution and structure prediction. The TEM1 (β-lactamase) translocation assay was performed, which showed that EspN and EspS are translocated into host cells in a T3SS-dependent manner during bacterial infection. A phylogenetic tree analysis revealed that homologs of EspN and EspS are widely distributed in pathogenic bacteria. Multiple sequence alignment revealed that EspN and its homologs share a conserved C-terminal region (673-1133 a.a.). Furthermore, the structure of EspN (673-1133 a.a.) was also predicted and well-defined, which showed that it has three subdomains connected by a loop region. EspS and its homologs share a sequence-conserved C-terminal (146-291 a.a.). The predicted structure of EspS (146-291 a.a.) is composed of a β-sheet consisting of four β-strands and several short helices, which has a TM score of 0.5014 with the structure of the Vibrio cholerae RTX cysteine protease domain (PDBID: 3eeb). These results suggest that EspN and EspS may represent two important classes of T3SS effectors associated with pathogen virulence, and our findings provide important clues to understanding the potential functions of EspN and EspS.

Impact of phylogeny on the inference of functional sectors from protein sequence data.

Statistical analysis of multiple sequence alignments of homologous proteins has revealed groups of coevolving amino acids called sectors. These groups of amino-acid sites feature collective correlations in their amino-acid usage, and they are associated to functional properties. Modeling showed that nonlinear selection on an additive functional trait of a protein is generically expected to give rise to a functional sector. These modeling results motivated a principled method, called ICOD, which is designed to identify functional sectors, as well as mutational effects, from sequence data. However, a challenge for all methods aiming to identify sectors from multiple sequence alignments is that correlations in amino-acid usage can also arise from the mere fact that homologous sequences share common ancestry, i.e. from phylogeny. Here, we generate controlled synthetic data from a minimal model comprising both phylogeny and functional sectors. We use this data to dissect the impact of phylogeny on sector identification and on mutational effect inference by different methods. We find that ICOD is most robust to phylogeny, but that conservation is also quite robust. Next, we consider natural multiple sequence alignments of protein families for which deep mutational scan experimental data is available. We show that in this natural data, conservation and ICOD best identify sites with strong functional roles, in agreement with our results on synthetic data. Importantly, these two methods have different premises, since they respectively focus on conservation and on correlations. Thus, their joint use can reveal complementary information.

Advancing microbial diagnostics: a universal phylogeny guided computational algorithm to find unique sequences for precise microorganism detection.

Sequences derived from organisms sharing common evolutionary origins exhibit similarity, while unique sequences, absent in related organisms, act as good diagnostic marker candidates. However, the approach focused on identifying dissimilar regions among closely-related organisms poses challenges as it requires complex multiple sequence alignments, making computation and parsing difficult. To address this, we have developed a biologically inspired universal NAUniSeq algorithm to find the unique sequences for microorganism diagnosis by traveling through the phylogeny of life. Mapping through a phylogenetic tree ensures a low number of cross-contamination and false positives. We have downloaded complete taxonomy data from Taxadb database and sequence data from National Center for Biotechnology Information Reference Sequence Database (NCBI-Refseq) and, with the help of NetworkX, created a phylogenetic tree. Sequences were assigned over the graph nodes, k-mers were created for target and non-target nodes and search was performed over the graph using the depth first search algorithm. In a memory efficient alternative NoSQL approach, we created a collection of Refseq sequences in MongoDB database using tax-id and path of FASTA files. We queried the MongoDB collection for the target and non-target sequences. In both the approaches, we used an alignment free sliding window k-mer-based procedure that quickly compares k-mers of target and non-target sequences and returns unique sequences that are not present in the non-target. We have validated our algorithm with target nodes Mycobacterium tuberculosis, Neisseria gonorrhoeae, and Monkeypox and generated unique sequences. This universal algorithm is a powerful tool for generating diagnostic sequences, enabling the accurate identification of microbial strains with high phylogenetic precision.

CRISPR/Cas12a-Based Indirect Competitive Enzyme-Linked Immunosorbent Assay for Sensitive Detection of Ochratoxin A.

The high toxicity and widespread contamination of ochratoxin A (OTA) make it urgent to develop a sensitive method to detect trace OTA in complex food matrices. Herein, an indirect competitive enzyme-linked immunosorbent assay (icELISA)-based on the CRISPR/Cas12a system is described. DNA amplicons with multiple activation sequences of the CRISPR/Cas12a system were pre-prepared to improve detection sensitivity. In the absence of OTA, streptavidin-mediated biotinylated DNA amplicons were captured by the biotinylated secondary antibody on the microplate. The captured DNA amplicons activated the CRISPR/Cas12a system, which thereby effectively cleaved the reporter DNA, producing strong fluorescence. The presence of OTA led to a decrease in DNA amplicons on the microplate, resulting in a decrease in activated Cas12a and ultimately a drop in fluorescence intensity. OTA in food matrices at nanogram per milliliter levels can be detected. Therefore, the new method has great potential in monitoring OTA.