Decoding molecular features of bovine oocyte fate during antral follicle growth via single-cell multi-omics analysis.

Antral follicle size is a useful predictive marker of the competency of enclosed oocytes for yielding an embryo following in vitro maturation and fertilization. However, the molecular mechanisms underpinning oocyte developmental potential during bovine antral follicle growth are still unclear. Here, we used a modified single-cell multi-omics approach to analyze the transcriptome, DNA methylome and chromatin accessibility in parallel for oocytes and cumulus cells collected from bovine antral follicles of different sizes. Transcriptome profiling identified three types of oocytes (Small, Medium and Large) that underwent different developmental trajectories, with Large oocytes exhibiting the largest average follicle size and characteristics resembling metaphase-II oocytes. Differential expression analysis and real-time PCR assay showed that most replication-dependent histone genes were highly expressed in Large oocytes. The joint analysis of multi-omics data revealed that the transcription of 20 differentially expressed genes in Large oocytes was associated with both DNA methylation and chromatin accessibility. In addition, oocyte-cumulus interaction analysis showed that inflammation, DNA damage, and p53 signaling pathways were active in Small oocytes, which had the smallest average follicle sizes. We further confirmed that p53 pathway inhibition in in vitro maturation experiments using oocytes obtained from small antral follicles could improve the quality of oocytes and increased the blastocyte rate after in vitro fertilization and culture. Our work provides new insights into the intricate orchestration of bovine oocyte fate determination during antral folliculogenesis, which is instrumental for optimizing in vitro maturation techniques to optimize oocyte quality.

Multi-omics reveal the gut microbiota-mediated severe foraging environment adaption of small wild ruminants in the Three-River-Source National Park, China.

The Tibetan antelope (Pantholops hodgsonii), blue sheep (Pseudois nayaur), and Tibetan sheep (Ovis aries) are the dominant small ruminants in the Three-River-Source National Park (TRSNP). However, knowledge about the association between gut microbiota and host adaptability remains poorly understood. Herein, multi-omics sequencing approaches were employed to investigate the gut microbiota-mediated forage adaption in these ruminants. The results revealed that although wild ruminants (WR) of P. hodgsoni and P. nayaur were faced with severe foraging environments with significantly low vegetation coverage and nutrition, the apparent forage digestibility of dry matter, crude protein, and acid detergent fiber was significantly higher than that of O. aries. The 16s rRNA sequencing showed that the gut microbiota in WR underwent convergent evolution, and alpha diversity in these two groups was significantly higher than that in O. aries. Moreover, indicator species, including Bacteroidetes and Firmicutes, exhibited positive relationships with apparent forage digestibility, and their relative abundances were enriched in the gut of WR. Enterotype analysis further revealed that enterotype 1 belonged to WR, and the abundance of fatty acid synthesis metabolic pathway-related enzyme genes was significantly higher than enterotype 2, represented by O. aries. Besides, the metagenomic analysis identified 14 pathogenic bacterial species, among which 10 potentially pathogenic bacteria were significantly enriched in the gut microbiota of O. aries. Furthermore, the cellulolytic strains and genes encoding cellulase and hemicellulase were significantly enriched in WR. In conclusion, our results provide new evidence of gut microbiota to facilitate wildlife adaption in severe foraging environments of the TRSNP, China.

Single-cell multi-omics sequencing reveals the immunological disturbance underlying STAT3-V637M Hyper-IgE syndrome.

Hyper-IgE syndrome (HIES) is a primary immunodeficiency characterized by, among others, the excessive production of IgE and repetitive bacterial/fungal infections. Mutations in STAT3, a transcription factor that orchestrates immune responses, may cause HIES, but the underlying mechanisms are not fully understood. Here, we used multi-omic approaches to comprehensively decipher the immune disturbance in a male HIES patient harboring STAT3-V637M. In his peripheral blood mononuclear cell (PBMC) we found significant clonal expansion of CD8 T cells (with increased CD8 subunits expression, potentially enhancing responsiveness to MHC I molecules), but not in his CD4 T cells and B cells. Although his B cells exhibited a higher potential in producing immunoglobulin, elevated SPIC binding might bias the products toward IgE isotype. Immune checkpoint inhibitors, including CTLA4, LAG3, were overexpressed in his PBMC-CD4 T cells, accompanied by reduced CD28 and IL6ST (gp130) expression. In his CD4 T cells, integrative analyses predicted upstream transcription factors (including ETV6, KLF13, and RORA) for LAG3, IL6ST, and CD28, respectively. The down-regulation of phagocytosis and nitric oxide synthesis-related genes in his PBMC-monocytes seem to be the culprit of his disseminated bacterial/fungal infection. Counterintuitively, in his PBMC we predicted increased STAT3 binding in both naïve and mature CD4 compartments, although this was not observed in most of his PBMC. In his bronchoalveolar lavage fluid (BALF), we found two macrophage subtypes with anti-bacterial properties, which were identified by CXCL8/S100A8/S100A9, or SOD2, respectively. Together, we described how the immune cell landscape was disturbed in STAT3-V637M HIES, providing a resource for further studies.

Spatial Omics Sequencing Based on Microfluidic Array Chips.

Spatial profiling technologies fill the gap left by the loss of spatial information in traditional single-cell sequencing, showing great application prospects. After just a few years of quick development, spatial profiling technologies have made great progress in resolution and simplicity. This review introduces the development of spatial omics sequencing based on microfluidic array chips and describes barcoding strategies using various microfluidic designs with simplicity and efficiency. At the same time, the pros and cons of each strategy are compared. Moreover, commercialized solutions for spatial profiling are also introduced. In the end, the future perspective of spatial omics sequencing and research directions are discussed.

Spatially resolved expression landscape and gene-regulatory network of human gastric corpus epithelium.

Molecular knowledge of human gastric corpus epithelium remains incomplete. Here, by integrated analyses using single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, and single-cell assay for transposase accessible chromatin sequencing (scATAC-seq) techniques, we uncovered the spatially resolved expression landscape and gene-regulatory network of human gastric corpus epithelium. Specifically, we identified a stem/progenitor cell population in the isthmus of human gastric corpus, where EGF and WNT signaling pathways were activated. Meanwhile, LGR4, but not LGR5, was responsible for the activation of WNT signaling pathway. Importantly, FABP5 and NME1 were identified and validated as crucial for both normal gastric stem/progenitor cells and gastric cancer cells. Finally, we explored the epigenetic regulation of critical genes for gastric corpus epithelium at chromatin state level, and identified several important cell-type-specific transcription factors. In summary, our work provides novel insights to systematically understand the cellular diversity and homeostasis of human gastric corpus epithelium in vivo.

Technologies and applications of single-cell DNA methylation sequencing.

DNA methylation is the most stable epigenetic modification. In mammals, it usually occurs at the cytosine of CpG dinucleotides. DNA methylation is essential for many physiological and pathological processes. Aberrant DNA methylation has been observed in human diseases, particularly cancer. Notably, conventional DNA methylation profiling technologies require a large amount of DNA, often from a heterogeneous cell population, and provide an average methylation level of many cells. It is often not realistic to collect sufficient numbers of cells, such as rare cells and circulating tumor cells in peripheral blood, for bulk sequencing assays. It is therefore essential to develop sequencing technologies that can accurately profile DNA methylation using small numbers of cells or even single cells. Excitingly, many single-cell DNA methylation sequencing and single-cell omics sequencing technologies have been developed, and applications of these methods have greatly expanded our understanding of the molecular mechanism of DNA methylation. Here, we summaries single-cell DNA methylation and multi-omics sequencing methods, delineate their applications in biomedical sciences, discuss technical challenges, and present our perspective on future research directions.

Deciphering the biodesulfurization pathway employing marine mangrove Bacillus aryabhattai strain NM1-A2 according to whole genome sequencing and transcriptome analyses.

In the biogeochemical cycle, sulfur oxidation plays a vital role and is typically referred to as the elemental sulfur or reductive sulfide oxidation process. This study aimed to characterize a subtropical mangrove-isolated bacterial strain using biochemical, whole-genome, and transcriptome sequencing analyses to enhance our understanding of sulfur metabolism and biodegradation from a molecular genetic perspective. Strain NM1-A2 was characterized as Gram-positive and found to have a close molecular phylogenetic relationship with Bacillus aryabhattai. NM1-A2 efficiently converted dibenzothiophene (DBT) into 2-hydroxybiphenyl (2-HBP) via a 4S pathway with 95% efficiency, using enzymes encoded by the dsz operon (dszA, dszB, and dszC), which determine monooxygenases (DszA & DszC) and desulfinase (DszB). The whole-genome sequence of NM1-A2 had a length of approximately 5,257,678 bp and included 16 sulfur metabolism-related genes, featuring the ABC transport system, small subunit (ssu) and cysteine (cys) gene families, and adenosine 5'-phosphosulfate (APS) and 3'-phosphoadenosine-5'-phosphosulfate (PAPS) biosynthesis-related genes. Transcriptomic analysis of NM1-A2 using three sulfur groups-magnesium sulfate (MS), sulfur powder (SP), and sodium thiosulfate (ST) resulted in a significant number of differentially expressed genes (1200, 2304, and 2001, respectively). This analysis revealed that intracellular cysteine concentration directly regulated the expression of cys and ssu genes. Sulfate did not directly affect cys gene expression but repressed ssu gene expression. The cys gene expression levels decreased during the conversion of sulfate to sulfide and cysteine. The transcriptomic data was validated by analyzing the expression patterns of NM1-A2 using real-time quantitative PCR validation analysis. The expression levels of cysl, mccB, and nrnA were significantly upregulated, while cysH, metB, and sat were downregulated in the SP, ST, and MS groups, respectively. This research contributes to our understanding of marine mangrove microorganisms' bacterial efficiency through characterization, whole-genome, and transcriptome sequencing-based molecular degradation of organic compounds in the mangrove ecosystem, which may enhance nutrient availability.

Single-cell multi-omics sequencing and its application in tumor heterogeneity.

In recent years, the emergence and development of single-cell sequencing technologies have provided unprecedented opportunities to analyze deoxyribonucleic acid, ribonucleic acid and proteins at single-cell resolution. The advancements and reduced costs of high-throughput technologies allow for parallel sequencing of multiple molecular layers from a single cell, providing a comprehensive insight into the biological state and behavioral mechanisms of cells through the integration of genomics, transcriptomics, epigenomics and proteomics information. Researchers are actively working to further improve the cost-effectiveness, stability and high-throughput capabilities of single-cell multi-omics sequencing technologies and exploring their potential in precision medicine through clinical diagnostics. This review aims to survey the cutting-edge advancements in single-cell multi-omics sequencing, summarizing the representative technologies and their applications in profiling complex diseases, with a particular focus on tumors.

Spatially resolved expression landscape and gene-regulatory network of human gastric corpus epithelium

Molecular knowledge of human gastric corpus epithelium remains incomplete. Here, by integrated analyses using single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, and single-cell assay for transposase accessible chromatin sequencing (scATAC-seq) techniques, we uncovered the spatially resolved expression landscape and gene-regulatory network of human gastric corpus epithelium. Specifically, we identified a stem/progenitor cell population in the isthmus of human gastric corpus, where EGF and WNT signaling pathways were activated. Meanwhile, LGR4, but not LGR5, was responsible for the activation of WNT signaling pathway. Importantly, FABP5 and NME1 were identified and validated as crucial for both normal gastric stem/progenitor cells and gastric cancer cells. Finally, we explored the epigenetic regulation of critical genes for gastric corpus epithelium at chromatin state level, and identified several important cell-type-specific transcription factors. In summary, our work provides novel insights to systematically understand the cellular diversity and homeostasis of human gastric corpus epithelium in vivo.

Computational solutions for spatial transcriptomics.

Transcriptome level expression data connected to the spatial organization of the cells and molecules would allow a comprehensive understanding of how gene expression is connected to the structure and function in the biological systems. The spatial transcriptomics platforms may soon provide such information. However, the current platforms still lack spatial resolution, capture only a fraction of the transcriptome heterogeneity, or lack the throughput for large scale studies. The strengths and weaknesses in current ST platforms and computational solutions need to be taken into account when planning spatial transcriptomics studies. The basis of the computational ST analysis is the solutions developed for single-cell RNA-sequencing data, with advancements taking into account the spatial connectedness of the transcriptomes. The scRNA-seq tools are modified for spatial transcriptomics or new solutions like deep learning-based joint analysis of expression, spatial, and image data are developed to extract biological information in the spatially resolved transcriptomes. The computational ST analysis can reveal remarkable biological insights into spatial patterns of gene expression, cell signaling, and cell type variations in connection with cell type-specific signaling and organization in complex tissues. This review covers the topics that help choosing the platform and computational solutions for spatial transcriptomics research. We focus on the currently available ST methods and platforms and their strengths and limitations. Of the computational solutions, we provide an overview of the analysis steps and tools used in the ST data analysis. The compatibility with the data types and the tools provided by the current ST analysis frameworks are summarized.

Single-cell Sequencing Reveals Clearance of Blastula Chromosomal Mosaicism in In Vitro Fertilization Babies.

Although chromosomal mosaic embryos detected by trophectoderm (TE) biopsy offer healthy embryos available for transfer, high-resolution postnatal karyotyping and chromosome testing of the transferred embryos are insufficient. Here, we applied single-cell multi-omics sequencing for seven infants with blastula chromosomal mosaicism detected by TE biopsy. The chromosome ploidy was examined by single-cell genome analysis, with the cellular identity being identified by single-cell transcriptome analysis. A total of 1616 peripheral leukocytes from seven infants with embryonic chromosomal mosaicism and three control ones with euploid TE biopsy were analyzed. A small number of blood cells showed copy number alterations (CNAs) on seemingly random locations at a frequency of 0%-2.5% per infant. However, none of the cells showed CNAs that were the same as those of the corresponding TE biopsies. The blastula chromosomal mosaicism may be fully self-corrected, probably through the selective loss of the aneuploid cells during development, and the transferred embryos can be born as euploid infants without mosaic CNAs corresponding to the TE biopsies. The results provide a new reference for the evaluations of transferring chromosomal mosaic embryos in certain situations.

How Did Institut Pasteur's NGS Core Facility, Biomics, Manage the Coronavirus Disease 2019 Crisis?

In 2020, research entities at the Institut Pasteur (IP) in Paris, as elsewhere around the world, were closed because of the coronavirus disease 2019 (COVID-19) pandemic. However, IP core facilities, laboratories, services, and departments working on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and priority projects were authorized to continue working both on site and remotely. Given the importance of its role in SARS-CoV-2 genome-sequencing initiatives, the IP Biomics core facility was fully functional during the first (i.e., March-June 2020) and second (i.e., November-December 2020) national lockdowns. We describe here how Biomics successfully implemented an emergency management plan to deal with this health crisis. We highlight the internal deployment of the institutional business continuity plan (BCP) through a series of actions. We also address the impact of the COVID-19 crisis on Biomics staff and collaborators. The added value of quality management and the limitations of risk management systems are discussed. Finally, we suggest that the Biomics infrastructure and the BCP described here could be used for benchmarking purposes, for other next-generation sequencing core facilities wishing to implement/improve their processes, and for future major crisis management.

Single-cell multi-omics sequencing: application trends, COVID-19, data analysis issues and prospects.

Single-cell sequencing is a biotechnology to sequence one layer of genomic information for individual cells in a tissue sample. For example, single-cell DNA sequencing is to sequence the DNA from every single cell. Increasing in complexity, single-cell multi-omics sequencing, or single-cell multimodal omics sequencing, is to profile in parallel multiple layers of omics information from a single cell. In practice, single-cell multi-omics sequencing actually detects multiple traits such as DNA, RNA, methylation information and/or protein profiles from the same cell for many individuals in a tissue sample. Multi-omics sequencing has been widely applied to systematically unravel interplay mechanisms of key components and pathways in cell. This survey overviews recent developments in single-cell multi-omics sequencing, and their applications to understand complex diseases in particular the COVID-19 pandemic. We also summarize machine learning and bioinformatics techniques used in the analysis of the intercorrelated multilayer heterogeneous data. We observed that variational inference and graph-based learning are popular approaches, and Seurat V3 is a commonly used tool to transfer the missing variables and labels. We also discussed two intensively studied issues relating to data consistency and diversity and commented on currently cared issues surrounding the error correction of data pairs and data imputation methods. The survey is concluded with some open questions and opportunities for this extraordinary field.

How orthodontic research can be enriched and advanced by the novel and promising evolutions in biomedicine.

Recent advances in developmental, molecular and cellular biology as well as biomedical technologies show a promising future for crossing the gap between biomedical basic sciences and clinical orthodontics. Orthodontic research shall utilise the advances and technologies in biomedical fields including genomics, molecular biology, bioinformatics and developmental biology. This review provides an update on the novel and promising evolutions in biomedicine and highlights their current and likely future implementation to orthodontic practice. Biotechnological opportunities in orthodontics and dentofacial orthopaedics are presented with regards to CRISPR technology, multi-omics sequencing, gene therapy, stem cells and regenerative medicine. Future orthodontic advances in terms of translational research are also discussed. Given the breadth of applications and the great number of questions that the presently available novel biomedical tools and techniques raise, their use may provide orthodontic research in the future with a great potential in understanding the aetiology of dentofacial deformities and malocclusions as well as in improving the practice of this clinical specialty.