Seqtometry (sequencing-to-measurement) is an analytical platform for single-cell analysis based on direct profiling of gene expression and accessibility achieved by advanced scoring with gene signatures. Here, we present a protocol for single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) analysis using Seqtometry. We describe steps for preprocessing, imputation, scoring, and plotting, with extensions to large datasets and integration of multiple datasets. This protocol yields results in the form of biologically interpretable dimensions for direct identification and comprehensive characterization of specific cells. For complete details on the use and execution of this protocol, please refer to Kousnetsov et al.1.

5-Methylcytosine (m5c) is a modified cytosine base which is formed as the result of addition of methyl group added at position 5 of carbon. This modification is one of the most common PTM that used to occur in almost all types of RNA. The conventional laboratory methods do not provide quick reliable identification of m5c sites. However, the sequence data readiness has made it feasible to develop computationally intelligent models that optimize the identification process for accuracy and robustness. The present research focused on the development of in-silico methods built using deep learning models. The encoded data was then fed into deep learning models, which included gated recurrent unit (GRU), long short-term memory (LSTM), and bi-directional LSTM (Bi-LSTM). After that, the models were subjected to a rigorous evaluation process that included both independent set testing and 10-fold cross validation. The results revealed that LSTM-based model, m5c-iDeep, outperformed revealing 99.9 % accuracy while comparing with existing m5c predictors. In order to facilitate researchers, m5c-iDeep was also deployed on a web-based server which is accessible at https://taseersuleman-m5c-ideep-m5c-ideep.streamlit.app/.

Lumpy skin disease (LSD) is a viral disease predominantly affecting cattle caused by a poxvirus belonging to the capripoxvirus genus. Here, we present a protocol for next-generation sequencing of the LSD virus genome using an amplicon-based approach. We describe steps for DNA extraction, viral DNA enrichment, amplicon pooling and purification, and library preparation and pooling. We then detail procedures for sequencing and computational analysis. This protocol can be adapted to any Illumina sequencing platform as an accelerated and scalable system. For complete details on the use and execution of this protocol, please refer to Bhatt et al.1,2.

OBJECTIVE: Canine parvovirus enteritis (CPE) is a contagious viral disease of dogs caused by the canine parvovirus-2 (CPV-2) associated with high morbidity and mortality rates. CPV-2 has a high global evolutionary rate. Molecular characterization of CPV-2 and understanding its epidemiology are essential for controlling CPV-2 infections.
OBJECTIVE: This study examined the risk factors and survival outcomes of dogs infected with CPV-2. Molecular characterization of CPV-2 genotypes circulating in Egypt was performed to determine the evolution of CPV-2 nationally and globally.
METHODS: An age-matched case-control study was conducted on 47 control and 47 CPV-infected dogs. Conditional logistic regression analysis examined the association between the potential risk factors and CPE in dogs. Survival analysis was performed to determine the survival pattern of the infected dogs. Thirteen fecal samples from infected dogs were collected to confirm the CPV genotype by CPV-2 VP2 gene sequencing, assembly of nucleotide sequences, and phylogenic analysis.
RESULTS: Unvaccinated and roamer dogs had eight and 2.3 times higher risks of CPV infection than vaccinated dogs and non-roamer dogs, respectively. The risk of death from CPE was high among dogs without routine visits to veterinary clinics and among non-roamer dogs. Molecular characterization of CPV-2 confirmed its genotype identity and relationship with the CPV-2 c and b clade types.
CONCLUSIONS: This study highlights the potential factors for CPE control, especially vaccination and preventing dogs from roaming freely outside houses. Isolated CPV genotypes are closely related to southern Asian genotypes, suggesting a substantial opportunity for global transmission.

This study employs multichannel sequence analysis of data from the Survey of Health, Ageing, and Retirement in Europe to explore variations in the association between work-family life trajectories and women\'s mental health across European cohorts born between 1924 and 1965 within different policy contexts. It finds that trajectories characterized by prolonged employment and delayed familial commitments are generally associated with increased depressive symptoms. Notably, the strength of this association varies significantly across cohorts and is notably moderated by defamilization policies. These policies, which aim to reduce dependency on family for managing social risks, buffer mental health challenges in traditional family roles but are less effective for women in trajectories with delayed family formation. This investigation highlights the nuanced ways in which historical and cultural contexts alongside policy environments shape mental health outcomes at various life stages, offering valuable insights into our understanding of health disparities across the life course, with an emphasis on exposure to changing institutions.

To date, more than 20 species in the genus Cyclospora have been reported. Among them, Cyclospora cayetanensis has been recognized as the causative agent of human cyclosporiasis, which is characterized by severe intestinal injury and prolonged diarrhea in patients with immune dysfunction. The presence of C. cayetanensis in cattle has been confirmed. To date, however, no surveillance data are available on the occurrence and prevalence of Cyclospora spp. in cattle in Shanxi Province, North China. In the present study, a total of 761 fecal samples collected from cattle in three representative counties (Qi, Jishan, and Shanyin) in this Province were examined for Cyclospora spp. by using a polymerase-chain-reaction-restriction-fragment-length polymorphism (PCR-RFLP) test based on the nuclear small subunit ribosomal RNA (SSU rRNA) gene. The prevalence of Cyclospora spp. in cattle was 2.1%, and region, age, sex, and breed were not identified to be risk factors. Molecular evolutionary analysis based on the SSU rRNA sequences revealed that all 12 of the isolates were relatively distant from the human pathogen C. cayetanensis; seven isolates were grouped with Cyclospora colobi, whereas the others were grouped with cattle Cyclospora spp. reported previously. Though C. cayetanensis was not detected in cattle in the present study, more investigations should be performed in human populations, other animal species, or cattle from other regions of Shanxi Province and other environmental sources from the One Health perspective.

Single-nuclei RNA sequencing (snRNA-seq) allows for obtaining gene expression profiles from frozen or hard-to-dissociate tissues at the single-nuclei level. Here, we describe a protocol to obtain snRNA-seq data of pancreatic tumors from orthotopically grafted organoid-derived mouse models. We provide details on the establishment of these mouse models, the isolation of single nuclei from pancreatic tumors, and the analysis of the snRNA-seq datasets. For complete details on the use and execution of this protocol, please refer to Mucciolo et al.1.

Ab initio computational reconstructions of protein-protein interaction (PPI) networks will provide invaluable insights into cellular systems, enabling the discovery of novel molecular interactions and elucidating biological mechanisms within and between organisms. Leveraging the latest generation protein language models and recurrent neural networks, we present SENSE-PPI, a sequence-based deep learning model that efficiently reconstructs ab initio PPIs, distinguishing partners among tens of thousands of proteins and identifying specific interactions within functionally similar proteins. SENSE-PPI demonstrates high accuracy, limited training requirements, and versatility in cross-species predictions, even with non-model organisms and human-virus interactions. Its performance decreases for phylogenetically more distant model and non-model organisms, but signal alteration is very slow. In this regard, it demonstrates the important role of parameters in protein language models. SENSE-PPI is very fast and can test 10,000 proteins against themselves in a matter of hours, enabling the reconstruction of genome-wide proteomes.

When inferring the evolution of a gene/gene family, it is advisable to use all available coding sequences (CDS) from as many species genomes as possible in order to infer and date all gene duplications and losses. Nowadays, this means using hundreds or even thousands of CDSs, which makes the inferred phylogenetic trees difficult to visualize and interpret. Therefore, it is useful to have an automated way of collapsing large phylogenetic trees according to a taxonomic term decided by the user (family, class, or order, for instance), in order to highlight the minimal set of sequences that should be used to recapitulate the full history of the gene/gene family being studied at that taxonomic level, that can be refined using additional software. Here we present the Phylogenetic Tree Collapser (PTC) program (https://github.com/pegi3s/phylogenetic-tree-collapser), a flexible tool for automated tree collapsing using taxonomic information, that can be easily used by researchers without a background in informatics, since it only requires the installation of Docker, Podman or Singularity. The utility of PTC is demonstrated by addressing the evolution of the ascorbic acid synthesis pathway in insects. A Docker image is available at Docker Hub (https://hub.docker.com/r/pegi3s/phylogenetic-tree-collapser) with PTC installed and ready-to-run.

BACKGROUND: Allergic fungal rhinosinusitis (AFRS) is a severe phenotype of chronic rhinosinusitis with nasal polyposis (CRSwNP), characterised by localised and exaggerated type 2 inflammation. While fungal antigenic stimulation of unregulated Th2-mediated inflammation is the core pathophysiological mechanism, the direct and synergistic role of bacteria in disease modification is a pervasive hypothesis. We set out to define the microenvironment of AFRS to elucidate virulent organisms that may be implicated in the pathophysiology of AFRS.
METHODS: We undertook a cross-sectional study of AFRS patients and non-fungal CRSwNP patients. Demographics, disease severity, culture and microbiome sequences were analysed. Multimodality microbiome sequencing included short-read next-generation sequencing (NGS) on the Illumina Miseq (16S rRNA and ITS) and full-length 16S rRNA sequencing on the Oxford Nanopore Technologies GridION (ONT).
RESULTS: Thirty-two AFRS and 29 non-fungal CRSwNP patients (NF) were included in this study. Staphylococcus aureus was the dominant organism cultured and sequenced in both AFRS and NF groups (AFRS 27.54%; NF 18.04%; p = .07). Streptococcus pneumoniae (AFRS 12.31%; NF 0.98%; p = .03) and Haemophilus influenzae (AFRS 15.03%; NF 0.24%; p = .005) were significantly more abundant in AFRS. Bacterial diversity (Shannon\'s index) was considerably lower in AFRS relative to NF (AFRS 0.6; NF 1.0, p = .008). Aspergillus was the most cultured fungus in AFRS (10/32, 31.3%). The AFRS sequenced mycobiome was predominantly represented by Malassezia (43.6%), Curvularia (18.5%) and Aspergillus (16.8%), while the NF mycobiome was nearly exclusively Malassezia (84.2%) with an absence of Aspergillus or dematiaceous fungi.
CONCLUSIONS: A low diversity, dysbiotic microenvironment dominated by Staphylococcus aureus, Streptococcus pneumoniae and Haemophilus influenzae characterised the bacterial microbiome of AFRS, with a mycobiome abundant in Malassezia, Aspergillus and Curvularia. While Staphylococcus aureus has been previously implicated in AFRS through enterotoxin superantigen potential, Streptococcus pneumoniae and Haemophilus influenzae are novel findings that may represent alternate cross-kingdom pathophysiological mechanisms.