Cyclosporine A (CsA) has shown efficacy against immunity-related diseases despite its toxicity in various organs, including the liver, emphasizing the need to elucidate its underlying hepatotoxicity mechanism. This study aimed to capture the alterations in genome-wide expression over time and the subsequent perturbations of corresponding pathways across species. Six data from humans, mice, and rats, including animal liver tissue, human liver microtissues, and two liver cell lines exposed to CsA toxic dose, were used. The microtissue exposed to CsA for 10 d was analyzed to obtain dynamically differentially expressed genes (DEGs). Single-time points data at 1, 3, 5, 7, and 28 d of different species were used to provide additional evidence. Using liver microtissue-based longitudinal design, DEGs that were consistently up- or down-regulated over time were captured, and the well-known mechanism involved in CsA toxicity was elucidated. Thirty DEGs that consistently changed in longitudinal data were also altered in 28-d rat in-house data with concordant expression. Some genes (e.g. TUBB2A, PLIN2, APOB) showed good concordance with identified DEGs in 1-d and 7-d mouse data. Pathway analysis revealed up-regulations of protein processing, asparagine N-linked glycosylation, and cargo concentration in the endoplasmic reticulum. Furthermore, the down-regulations of pathways related to biological oxidations and metabolite and lipid metabolism were elucidated. These pathways were also enriched in single-time-point data and conserved across species, implying their biological significance and generalizability. Overall, the human organoids-based longitudinal design coupled with cross-species validation provides temporal molecular change tracking, aiding mechanistic elucidation and biologically relevant biomarker discovery.

SUMMARYSeveral examples of high-impact cross-species transmission of newly emerging or re-emerging bat-borne viruses, such as Sudan virus, Nipah virus, and severe acute respiratory syndrome coronavirus 2, have occurred in the past decades. Recent advancements in next-generation sequencing have strengthened ongoing efforts to catalog the global virome, in particular from the multitude of different bat species. However, functional characterization of these novel viruses and virus sequences is typically limited with regard to assessment of their cross-species potential. Our understanding of the intricate interplay between virus and host underlying successful cross-species transmission has focused on the basic mechanisms of entry and replication, as well as the importance of host innate immune responses. In this review, we discuss the various roles of the respective molecular mechanisms underlying cross-species transmission using different recent bat-borne viruses as examples. To delineate the crucial cellular and molecular steps underlying cross-species transmission, we propose a framework of overall characterization to improve our capacity to characterize viruses as benign, of interest, or of concern.

Disruption of the thyroid hormone (TH) system is connected with diverse adverse health outcomes in wildlife and humans. It is crucial to develop and validate suitable in vitro assays capable of measuring the disruption of the thyroid hormone (TH) system. These assays are also essential to comply with the 3R principles, aiming to replace the ex vivo tests often utilised in the chemical assessment. We compared the two commonly used assays applicable for high throughput screening [Luminol and Amplex UltraRed (AUR)] for the assessment of inhibition of thyroid peroxidase (TPO, a crucial enzyme in TH synthesis) using several cell lines and 21 compounds from different use categories. As the investigated cell lines derived from human and rat thyroid showed low or undetectable TPO expression, we developed a series of novel cell lines overexpressing human TPO protein. The HEK-TPOA7 model was prioritised for further research based on the high and stable TPO gene and protein expression. Notably, the Luminol assay detected significant peroxidase activity and signal inhibition even in Nthy-ori 3-1 and HEK293T cell lines without TPO expression, revealing its lack of specificity. Conversely, the AUR assay was specific to TPO activity. Nevertheless, despite the different specificity, both assays identified similar peroxidation inhibitors. Over half of the tested chemicals with diverse structures and from different use groups caused TPO inhibition, including some widespread environmental contaminants suggesting a potential impact of environmental chemicals on TH synthesis. Furthermore, in silico SeqAPASS analysis confirmed the high similarity of human TPO across mammals and other vertebrate classes, suggesting the applicability of HEK-TPOA7 model findings to other vertebrates.

UNASSIGNED: Gout is the most common inflammatory arthritis in adults. Gout is an arthritic disease caused by the deposition of monosodium urate crystal (MSU) in the joints, which can lead to acute inflammation and damage adjacent tissue. Hyperuricemia is the main risk factor for MSU crystal deposition and gout. With the increasing burden of gout disease, the identification of potential biomarkers and novel targets for diagnosis is urgently needed.
UNASSIGNED: For the analysis of this subject paper, we downloaded the human gout data set GSE160170 and the gout mouse model data set GSE190138 from the GEO database. To obtain the differentially expressed genes (DEGs), we intersected the two data sets. Using the cytohubba algorithm, we identified the key genes and enriched them through GO and KEGG. The gene expression trends of three subgroups (normal control group, intermittent gout group and acute gout attack group) were analyzed by Series Test of Cluster (STC) analysis, and the key genes were screened out, and the diagnostic effect was verified by ROC curve. The expression of key genes in dorsal root nerve and spinal cord of gout mice was analyzed. Finally, the clinical samples of normal control group, hyperuricemia group, intermittent gout group and acute gout attack group were collected, and the expression of key genes at protein level was verified by ELISA.
UNASSIGNED: We obtained 59 co-upregulated and 28 co-downregulated genes by comparing the DEGs between gout mouse model data set and human gout data set. 7 hub DEGs(IL1B, IL10, NLRP3, SOCS3, PTGS2) were screened out via Cytohubba algorithm. The results of both GO and KEGG enrichment analyses indicate that 7 hub genes play a significant role in regulating the inflammatory response, cytokine production in immune response, and the TNF signaling pathway. The most representative hub genes SOCS3 and PTGS2 were screened out by Series Test of Cluster, and ROC analysis results showed the AUC values were both up to 1.000. In addition, we found that PTGS2 expression was significantly elevated in the dorsal root ganglia and spinal cord in monosodium urate(MSU)-induced gout mouse model. The ELISA results revealed that the expression of SOCS3 and PTGS2 was notably higher in the acute gout attack and intermittent gout groups compared to the normal control group. This difference was statistically significant, indicating a clear distinction between the groups.
UNASSIGNED: Through cross-species comprehensive analysis and experimental verification, SOCS3 and PTGS2 were proved to be new biomarkers for diagnosing gout and predicting disease progression.

High titers of anti-NMDAR1 autoantibodies in human brain cause anti-NMDAR1 encephalitis, a rare disease that displays a variety of psychiatric symptoms and neurological symptoms. Currently, immunohistochemical staining and cell-based assays are the standard methods for detection and semi-quantification of the anti-NMDAR1 autoantibodies. Low titers of blood circulating anti-NMDAR1 autoantibodies have been reported in a significant subset of the general human population. However, detection and quantification of these low titers of blood circulating anti-NMDAR1 autoantibodies are problematic because of high non-specific background from less diluted serum/plasma. Development of a new method to quantify these low titers of blood anti-NMDAR1 autoantibodies is necessary to understand their potential impacts on psychiatric symptoms and cognition. Based on our previous One-Step assay, we report the development of a novel simple immunoassay to quantify cross-species blood anti-NMDAR1 autoantibodies, and its validation with immunohistochemistry and cell-based assays in both humans and mice.

For canine parvovirus -2 (CPV-2), a zoonotic virus capable of cross-species transmission in animals, the amino acid changes of capsid protein VP2 are key factors when binding to other species\' transferrin receptors (TfR). CPV-2 variants can spread from felines and canines, for example, to Carnivora, Artiodactyla, and Pholidota species, and CPV-2c variants are essential to spread from Carnivora to Artiodactyla and Pholidota species in particular. In our study, a CPV-2a variant maintained a relatively stable trend, and the proportion of CPV-2c gradually rose from 1980 to 2021. The VP2 amino acid sequence analysis showed that five amino acid mutations at 426E/D, 305H/D, and 297S may be necessary for the virus to bind to different host receptors. Meanwhile, receptor-binding loop regions and amino acid sites 87 L, 93 N, 232I, and 305Y were associated with CPV-2 cross-species transmission. The homology of TfRs in different hosts infected with CPV-2 ranged from 77.2 % to 99.0 %, and from pig to feline, canine, and humans was 80.7 %, 80.4 %, and 77.2 %, respectively. The amino acid residues of TfRs involved in the viral binding in those hosts are highly conserved, which suggests that CPV-2 may be capable of pig-to-human transmission. Our analysis of the origin, evolutionary trend, cross-species transmission dynamics, and genetic characteristics of CPV-2 when binding to host receptors provides a theoretical basis for further research on CPV-2\'s mechanism of cross-species transmission and for establishing an early warning and monitoring mechanism for the possible threat of CPV-2 to animal-human public security.

Identifying polyphenotype genes that simultaneously regulate important agronomic traits (e.g., plant height, yield, and disease resistance) is critical for developing novel high-quality crop varieties. Predicting the associations between genes and traits requires the organization and analysis of multi-dimensional scientific data. The existing methods for establishing the relationships between genomic data and phenotypic data can only elucidate the associations between genes and individual traits. However, there are relatively few methods for detecting elite polyphenotype genes. In this study, a knowledge graph for traits regulating-genes was constructed by collecting data from the PubMed database and eight other databases related to the staple food crops rice, maize, and wheat as well as the model plant Arabidopsis thaliana. On the basis of the knowledge graph, a model for predicting traits regulating-genes was constructed by combining the data attributes of the gene nodes and the topological relationship attributes of the gene nodes. Additionally, a scoring method for predicting the genes regulating specific traits was developed to screen for elite polyphenotype genes. A total of 125,591 nodes and 547,224 semantic relationships were included in the knowledge graph. The accuracy of the knowledge graph-based model for predicting traits regulating-genes was 0.89, the precision rate was 0.91, the recall rate was 0.96, and the F1 value was 0.94. Moreover, 4,447 polyphenotype genes for 31 trait combinations were identified, among which the rice polyphenotype gene IPA1 and the A. thaliana polyphenotype gene CUC2 were verified via a literature search. Furthermore, the wheat gene TraesCS5A02G275900 was revealed as a potential polyphenotype gene that will need to be further characterized. Meanwhile, the result of venn diagram analysis between the polyphenotype gene datasets (consists of genes that are predicted by our model) and the transcriptome gene datasets (consists of genes that were differential expression in response to disease, drought or salt) showed approximately 70% and 54% polyphenotype genes were identified in the transcriptome datasets of Arabidopsis and rice, respectively. The application of the model driven by knowledge graph for predicting traits regulating-genes represents a novel method for detecting elite polyphenotype genes.

Especially for the production of artificial, difficult to express molecules a further development of the CHO production cell line is required to keep pace with the continuously increasing demands. However, the identification of novel targets for cell line engineering to improve CHO cells is a time and cost intensive process. Since plasma cells are evolutionary optimized for a high antibody expression in mammals, we performed a comprehensive multi-omics comparison between CHO and plasma cells to exploit optimized cellular production traits. Comparing the transcriptome, proteome, miRNome, surfaceome and secretome of both cell lines identified key differences including 392 potential overexpression targets for CHO cell engineering categorized in 15 functional classes like transcription factors, protein processing or secretory pathway. In addition, 3 protein classes including 209 potential knock-down/out targets for CHO engineering were determined likely to affect aggregation or proteolysis. For production phenotype engineering, several of these novel targets were successfully applied to transient and transposase mediated overexpression or knock-down strategies to efficiently improve productivity of CHO cells. Thus, substantial improvement of CHO productivity was achieved by taking nature as a blueprint for cell line engineering.

Over the last three years, the pandemic of COVID-19 has had a significant impact on people\'s lives and the global economy. The incessant emergence of variant strains has compounded the challenges associated with the management of COVID-19. As the predominant variant from late 2021 to the present, Omicron and its sublineages, through continuous evolution, have demonstrated iterative viral fitness. The comprehensive elucidation of the biological implications that catalyzed this evolution remains incomplete. In accordance with extant research evidence, we provide a comprehensive review of subvariants of Omicron, delineating alterations in immune evasion, cellular infectivity, and the cross-species transmission potential. This review seeks to clarify the underpinnings of biology within the evolution of SARS-CoV-2, thereby providing a foundation for strategic considerations in the post-pandemic era of COVID-19.

The global burden of early life adversity (ELA) is profound. The World Health Organization has estimated that ELA accounts for almost 30% of all psychiatric cases. Yet, our ability to identify which individuals exposed to ELA will develop mental illness remains poor and there is a critical need to identify underlying pathways and mechanisms. This review proposes unpredictability as an understudied aspect of ELA that is tractable and presents a conceptual model that includes biologically plausible mechanistic pathways by which unpredictability impacts the developing brain. The model is supported by a synthesis of published and new data illustrating the significant impacts of patterns of signals on child development. We begin with an overview of the existing unpredictability literature, which has focused primarily on longer patterns of unpredictability (e.g. years, months, and days). We then describe our work testing the impact of patterns of parental signals on a moment-to-moment timescale, providing evidence that patterns of these signals during sensitive windows of development influence neurocircuit formation across species and thus may be an evolutionarily conserved process that shapes the developing brain. Next, attention is drawn to emerging themes which provide a framework for future directions of research including the evaluation of functions, such as effortful control, that may be particularly vulnerable to unpredictability, sensitive periods, sex differences, cross-cultural investigations, addressing causality, and unpredictability as a pathway by which other forms of ELA impact development. Finally, we provide suggestions for prevention and intervention, including the introduction of a screening instrument for the identification of children exposed to unpredictable experiences.