Protein subcellular relocalization and function of duplicated flagellar calcium binding protein genes in honey bee trypanosomatid parasite.

The honey bee trypanosomatid parasite, Lotmaria passim, contains two genes that encode the flagellar calcium binding protein (FCaBP) through tandem duplication in its genome. FCaBPs localize in the flagellum and entire body membrane of L. passim through specific N-terminal sorting sequences. This finding suggests that this is an example of protein subcellular relocalization resulting from gene duplication, altering the intracellular localization of FCaBP. However, this phenomenon may not have occurred in Leishmania, as one or both of the duplicated genes have become pseudogenes. Multiple copies of the FCaBP gene are present in several Trypanosoma species and Leptomonas pyrrhocoris, indicating rapid evolution of this gene in trypanosomatid parasites. The N-terminal flagellar sorting sequence of L. passim FCaBP1 is in close proximity to the BBSome complex, while that of Trypanosoma brucei FCaBP does not direct GFP to the flagellum in L. passim. Deletion of the two FCaBP genes in L. passim affected growth and impaired flagellar morphogenesis and motility, but it did not impact host infection. Therefore, FCaBP represents a duplicated gene with a rapid evolutionary history that is essential for flagellar structure and function in a trypanosomatid parasite.

Aspartyl protease in the secretome of honey bee trypanosomatid parasite contributes to infection of bees.

BACKGROUND: The exoproteome, which consists of both secreted proteins and those originating from cell surfaces and lysed cells, is a critical component of trypanosomatid parasites, facilitating interactions with host cells and gut microbiota. However, its specific roles in the insect hosts of these parasites remain poorly understood. METHODS: We conducted a comprehensive characterization of the exoproteome in Lotmaria passim, a trypanosomatid parasite infecting honey bees, under culture conditions. We further investigated the functions of two conventionally secreted proteins, aspartyl protease (LpAsp) and chitinase (LpCht), as representative models to elucidate the role of the secretome in L. passim infection of honey bees. RESULTS: Approximately 48% of L. passim exoproteome proteins were found to share homologs with those found in seven Leishmania spp., suggesting the existence of a core exoproteome with conserved functions in the Leishmaniinae lineage. Bioinformatics analyses suggested that the L. passim exoproteome may play a pivotal role in interactions with both the host and its microbiota. Notably, the deletion of genes encoding two secretome proteins revealed the important role of LpAsp, but not LpCht, in L. passim development under culture conditions and its efficiency in infecting the honey bee gut. CONCLUSIONS: Our results highlight the exoproteome as a valuable resource for unraveling the mechanisms employed by trypanosomatid parasites to infect insect hosts by interacting with the gut environment.

Neural and behavioral evidence supporting the relationship between habitual exercise and working memory precision in healthy young adults.

Introduction: Working memory (WM) is a well-known fundamental ability related to various high-level cognitive functions, such as executive functioning, decision-making, and problem-solving. Although previous studies have posited that chronic exercise may improve cognitive functions, its underlying neural mechanisms and whether habitual exercise is associated with individual WM ability remain unclear. Methods: In the current study, 36 participants reported their habitual physical activity through the International Physical Activity Questionnaire (IPAQ). In addition to assessments of intelligence quotient (IQ), WM storage capacity (K score), and visuomotor coordination capacity, electroencephalogram (EEG) signals were recorded while the participants performed a WM precision task fusing conventional visual and motor retrospective cue (retro-cue) WM tasks. Results: We found that greater amounts of and higher frequencies of vigorous-intensity exercise were highly correlated with smaller recall errors in the WM precision task. Contralateral delay activity (CDA), a well-known WM-related event-related potential (ERP) component evoked by the valid retro-cue, predicted individual behavioral recall error. Participants who met the medium or high level of IPAQ criteria (the regular exercise group) showed smaller behavioral recall error and larger CDA than participants who did not meet the criteria (the irregular exercise group). The two groups did not differ in other assessments, such as IQ, WM storage capacity, and visuomotor coordination ability. Discussion: Habitual exercise was specifically correlated with individual differences in WM precision, rather than IQ, WM storage capacity, and visuomotor coordination ability, suggesting potential mechanisms of how modulations of chronic exercise improve cognition through visual and/or motor WM precision.

Evolutionary history of metazoan TMEM16 family.

Most of Transmembrane protein 16 (TMEM16) family members function as either a Ca2+-activated Cl- channel (CaCC) or phospholipid scramblase (CaPLSase) and play diverse physiological roles. It is well conserved in eukaryotes; however, the origin and evolution of different subfamilies in Metazoa are not yet understood. To uncover the evolutionary history of the TMEM16 family, we analyzed 398 proteins from 74 invertebrate species using evolutionary genomics. We found that the TMEM16C-F and J subfamilies are vertebrate-specific, but the TMEM16A/B, G, H, and K subfamilies are ancient and present in many, but not all metazoan species. The most ancient subfamilies in Metazoa, TMEM16L and M, are only maintained in limited species. TMEM16N and O are Cnidaria- and Ecdysozoa-specific subfamilies, respectively, and Ctenophora, Xenacoelomorpha, and Rotifera contain species-specific proteins. We also identified TMEM16 genes that are closely linked together in the genome, suggesting that they have been generated via recent gene duplication. The anoctamin domain structures of invertebrate-specific TMEM16 proteins predicted by AlphaFold2 contain conserved Ca2+-binding motifs and permeation pathways with either narrow or wide inner gates. The inner gate distance of TMEM16 protein may have frequently switched during metazoan evolution, and thus determined the function of the protein as either CaCC or CaPLSase. These results demonstrate that TMEM16 family has evolved by gene gain and loss in metazoans, and the genes have been generally under purifying selection to maintain protein structures and physiological functions.

DWV 3C Protease Uncovers the Diverse Catalytic Triad in Insect RNA Viruses.

Deformed wing virus (DWV) is the most prevalent Iflavirus that is infecting honey bees worldwide. However, the mechanisms of its infection and replication in host cells are poorly understood. In this study, we analyzed the structure and function of DWV 3C protease (3Cpro), which is necessary for the cleavage of the polyprotein to synthesize mature viral proteins. Thus, it is one of the nonstructural viral proteins essential for the replication. We found that the 3Cpros of DWV and picornaviruses share common enzymatic properties, including sensitivity to the same inhibitors, such as rupintrivir. The predicted structure of DWV 3Cpro by AlphaFold2, the predicted rupintrivir binding domain, and the protease activities of mutant proteins revealed that it has a Cys-His-Asn catalytic triad. Moreover, 3Cpros of other Iflaviruses and Dicistrovirus appear to contain Asn, Ser, Asp, or Glu as the third residue of the catalytic triad, suggesting diversity in insect RNA viruses. Both precursor 3Cpro with RNA-dependent RNA polymerase and mature 3Cpro are present in DWV-infected cells, suggesting that they may have different enzymatic properties and functions. DWV 3Cpro is the first 3Cpro characterized among insect RNA viruses, and our study uncovered both the common and unique characteristics among 3Cpros of Picornavirales. Furthermore, it would be possible to use the specific inhibitors of DWV 3Cpro to control DWV infection in honey bees in future. IMPORTANCE The number of managed honey bee (Apis mellifera) colonies has considerably declined in many developed countries in the recent years. Deformed wing virus (DWV) vectored by the mites is the major threat to honey bee colonies and health. To give insight into the mechanism of DWV replication in the host cells, we studied the structure-function relationship of 3C protease (3Cpro), which is necessary to cleave a viral polyprotein at the specific sites to produce the mature proteins. We found that the overall structure, some inhibitors, and processing of 3Cpro are shared between Picornavirales; however, there is diversity in the catalytic triad. DWV 3Cpro is the first viral protease characterized among insect RNA viruses and reveals the evolutionary history of 3Cpro among Picornavirales. Furthermore, DWV 3Cpro inhibitors identified in our study could also be applied to control DWV in honey bees in future.

DWV Infection in vitro Using Honey Bee Pupal Tissue.

The deformed wing virus (DWV) has been best characterized among honey bee viruses; however, very little is known regarding the mechanisms of viral infection and replication due to the lack of immortalized honey bee cell lines. To solve this problem, we established an in vitro system using honey bee pupal tissue to reconstruct DWV binding and entry into the host cell, followed by translation of the RNA genome and polyprotein processing using RNA-dependent RNA polymerase (RdRP) as a marker. Using this system, the P-domain of the virion subunit VP1 was found to be essential for DWV infection, but not for binding and entry into the cell. DWV efficiently infected the head tissue derived from early but not late pupa, suggesting that undifferentiated cells are targeted for viral infection. Furthermore, we found that inhibitors of mammalian picornavirus 3C-protease, rupintrivir and quercetin suppressed RdRP synthesis, indicating that this in vitro system is also useful for screening a compound to control viral infection. Our in vitro system may help to understand the mechanism of DWV infection in host cells.

FluReassort: a database for the study of genomic reassortments among influenza viruses.

Genomic reassortment is an important genetic event in the generation of emerging influenza viruses, which can cause numerous serious flu endemics and epidemics within hosts or even across different hosts. However, there is no dedicated and comprehensive repository for reassortment events among influenza viruses. Here, we present FluReassort, a database for understanding the genomic reassortment events in influenza viruses. Through manual curation of thousands of literature references, the database compiles 204 reassortment events among 56 subtypes of influenza A viruses isolated in 37 different countries. FluReassort provides an interface for the visualization and evolutionary analysis of reassortment events, allowing users to view the events through the phylogenetic analysis with varying parameters. The reassortment networks in FluReassort graphically summarize the correlation and causality between different subtypes of the influenza virus and facilitate the description and interpretation of the reassortment preference among subtypes. We believe FluReassort is a convenient and powerful platform for understanding the evolution of emerging influenza viruses. FluReassort is freely available at https://www.jianglab.tech/FluReassort.

Regulation of Early Host Immune Responses Shapes the Pathogenicity of Avian Influenza A Virus.

Avian influenza A viruses (IAV) can cross the species barrier and cause disease in humans. Understanding the pathogenesis of avian IAV remains a challenge. Interferon-mediated antiviral responses and multiple cytokines production are important host cellular antiviral immunity against IAV infection. To elucidate the pathogenicity of avian IAV, a system approach was adopted to investigate dysregulation of the two host cellular antiviral immune responses in contrast with human IAV. As a result, we revealed that avian IAV not only disrupted normal early host cellular interferon-mediated antiviral responses, but also caused abnormal cytokines production through different pathways. For avian IAV infection, dysregulation of STAT2 was mainly responsible for abnormal cellular interferon-mediated antiviral responses, and IRF5 and NFKB1 played crucial roles in unusual cytokines production. In contrast, for human IAV infection, IRF1, IRF7, and STAT1 contributed to cellular cytokines production. Furthermore, differential activation of pattern recognition receptors (PRRs) likely led to avian IAV-related abnormal early host cellular antiviral immunity, where TLR7 and RIG-I were activated by avian and human IAV, respectively. Finally, a pathogenesis model was proposed that combined of early host cellular interferon-mediated antiviral responses with cytokines production could partly explain the pathogenicity of avian IAV. In conclusion, our study provides a new perspective of the pathogenesis of avian IAV, which will be helpful in preventing their infections in the future.

Single-Cell Transcriptome Analysis of Uniparental Embryos Reveals Parent-of-Origin Effects on Human Preimplantation Development.

To investigate the contribution of parental genomes to early embryogenesis, we profiled the single-cell transcriptomes of human biparental and uniparental embryos systematically from the 1-cell to the morula stage. We observed that uniparental embryos exhibited variable and decreased embryonic genome activation (EGA). Comparative transcriptome analysis identified 807 maternally biased expressed genes (MBGs) and 581 paternally biased expressed genes (PBGs) in the preimplantation stages. MBGs became apparent at the 4-cell stage and contributed to the initiation of EGA, whereas PBGs preferentially appeared at the 8-cell stage and might affect embryo compaction and trophectoderm specification. Regulatory network analysis revealed that DUX4, EGR2, and DUXA are key transcription factors in MBGs' expression; ZNF263 and KLF3 are important for PBGs' expression. We demonstrated that parent-specific DNA methylation might account for the expression of most PBGs. Our results provide a valuable resource to understand parental genome activation and might help to elucidate parent-of-origin effects in early human development.

seq-ImmuCC: Cell-Centric View of Tissue Transcriptome Measuring Cellular Compositions of Immune Microenvironment From Mouse RNA-Seq Data.

The RNA sequencing approach has been broadly used to provide gene-, pathway-, and network-centric analyses for various cell and tissue samples. However, thus far, rich cellular information carried in tissue samples has not been thoroughly characterized from RNA-Seq data. Therefore, it would expand our horizons to better understand the biological processes of the body by incorporating a cell-centric view of tissue transcriptome. Here, a computational model named seq-ImmuCC was developed to infer the relative proportions of 10 major immune cells in mouse tissues from RNA-Seq data. The performance of seq-ImmuCC was evaluated among multiple computational algorithms, transcriptional platforms, and simulated and experimental datasets. The test results showed its stable performance and superb consistency with experimental observations under different conditions. With seq-ImmuCC, we generated the comprehensive landscape of immune cell compositions in 27 normal mouse tissues and extracted the distinct signatures of immune cell proportion among various tissue types. Furthermore, we quantitatively characterized and compared 18 different types of mouse tumor tissues of distinct cell origins with their immune cell compositions, which provided a comprehensive and informative measurement for the immune microenvironment inside tumor tissues. The online server of seq-ImmuCC are freely available at http://wap-lab.org:3200/immune/.

Network Biomarkers Constructed from Gene Expression and Protein-Protein Interaction Data for Accurate Prediction of Leukemia.

Leukemia is a leading cause of cancer deaths in the developed countries. Great efforts have been undertaken in search of diagnostic biomarkers of leukemia. However, leukemia is highly complex and heterogeneous, involving interaction among multiple molecular components. Individual molecules are not necessarily sensitive diagnostic indicators. Network biomarkers are considered to outperform individual molecules in disease characterization. We applied an integrative approach that identifies active network modules as putative biomarkers for leukemia diagnosis. We first reconstructed the leukemia-specific PPI network using protein-protein interactions from the Protein Interaction Network Analysis (PINA) and protein annotations from GeneGo. The network was further integrated with gene expression profiles to identify active modules with leukemia relevance. Finally, the candidate network-based biomarker was evaluated for the diagnosing performance. A network of 97 genes and 400 interactions was identified for accurate diagnosis of leukemia. Functional enrichment analysis revealed that the network biomarkers were enriched in pathways in cancer. The network biomarkers could discriminate leukemia samples from the normal controls more effectively than the known biomarkers. The network biomarkers provide a useful tool to diagnose leukemia and also aids in further understanding the molecular basis of leukemia.

Biomarker MicroRNAs for Diagnosis, Prognosis and Treatment of Hepatocellular Carcinoma: A Functional Survey and Comparison.

Hepatocellular Carcinoma (HCC) is one of the most common malignant tumors with high incidence and mortality rate. Precision and effective biomarkers are therefore urgently needed for the early diagnosis and prognostic estimation. MicroRNAs (miRNAs) are important regulators which play functions in various cellular processes and biological activities. Accumulating evidence indicated that the abnormal expression of miRNAs are closely associated with HCC initiation and progression. Recently, many biomarker miRNAs for HCC have been identified from blood or tissues samples, however, the universality and specificity on clinicopathological features of them are less investigated. In this review, we comprehensively surveyed and compared the diagnostic, prognostic, and therapeutic roles of HCC biomarker miRNAs in blood and tissues based on the cancer hallmarks, etiological factors as well as ethnic groups, which will be helpful to the understanding of the pathogenesis of biomarker miRNAs in HCC development and further provide accurate clinical decisions for HCC diagnosis and treatment.

Knowledge-Guided Bioinformatics Model for Identifying Autism Spectrum Disorder Diagnostic MicroRNA Biomarkers.

Autism spectrum disorder (ASD) is a severe neurodevelopmental disease with a high incidence and effective biomarkers are urgently needed for its diagnosis. A few previous studies have reported the detection of miRNA biomarkers for autism diagnosis, especially those based on bioinformatics approaches. In this study, we developed a knowledge-guided bioinformatics model for identifying autism miRNA biomarkers. We downloaded gene expression microarray data from the GEO Database and extracted genes with expression levels that differed in ASD and the controls. We then constructed an autism-specific miRNA-mRNA network and inferred candidate autism biomarker miRNAs based on their regulatory modes and functions. We defined a novel parameter called the autism gene percentage as autism-specific knowledge to further facilitate the identification of autism-specific biomarker miRNAs. Finally, 11 miRNAs were screened as putative autism biomarkers, where eight miRNAs (72.7%) were significantly dysregulated in ASD samples according to previous reports. Functional enrichment results indicated that the targets of the identified miRNAs were enriched in autism-associated pathways, such as Wnt signaling (in KEGG and IPA), cell cycle (in KEGG), and glioblastoma multiforme signaling (in IPA), thereby supporting the predictive power of our model.

LIMS and Clinical Data Management.

In order to achieve more accurate disease prevention, diagnosis, and treatment, clinical and genetic data need extensive and systematically associated study. As one way to achieve precision medicine, a laboratory information management system (LIMS) can effectively associate clinical data in a macrocosmic aspect and genomic data in a microcosmic aspect. This chapter summarizes the application of the LIMS in a clinical data management and implementation mode. It also discusses the principles of a LIMS in clinical data management, as well as the opportunities and challenges in the context of medical informatics.

Network-Based Biomedical Data Analysis.

Complex diseases are caused by disorders of both internal and external factors, and they account for a large proportion of human diseases. They are multigenetic and rarely a consequence of the dysfunction of single molecules. Systems biology views the living organism as an organic network. Compared with reductionism-based viewpoints, systems biology pays more attention to the interactions among molecules located at different omics levels. Based on this theory, the concepts of network biomarkers and network medicine have been proposed sequentially, which integrate clinical data with knowledge of network sciences, thereby promoting the investigation of disease pathogenesis in the era of biomedical informatics. The former aims to identify precise signals for disease diagnosis and prognosis, whereas the latter focuses on developing effective therapeutic strategies for specific patient cohorts. In this chapter, the basic concepts of systems biology and network theory are presented, and clinical applications of biomolecular networks, network biomarkers, and network medicine are then discussed.