The Functionally Unannotated Proteome of Human Male Tissues: A Shared Resource to Uncover New Protein Functions Associated with Reproductive Biology

Unveiling the characteristics of D4 and R4 aptamers for their future use in prostate cancer clinical practice

The DNA and RNA aptamers D4 and R4, respectively, emerged from the modification of PC-3 cell-binding aptamer A4. Our objective was to characterize the aptamers in silico and in vitro and begin to identify their target molecules. We represented their structures using computational algorithms; evaluated their binding to several prostate cell lines and their effects on the viability and migration of these cells; and determined their dissociation constant by flow cytometry. We analyzed circulating prostate tumor cells from patients using D4, R4, anti-CD133 and anti-CD44. Finally, the target proteins of both aptamers were precipitated and identified by mass spectrometry to simulate their in silico docking. The aptamers presented similar structures and bound to prostate tumor cells without modifying the cellular parameters studied, but with different affinities. The ligand cells for both aptamers were CD44+, indicating that they could identify cells in the mesenchymal stage of the metastatic process. The possible target proteins NXPE1, ADAM30, and MUC6 need to be further studied to better understand their interaction with the aptamers. These results support the development of new assays to determine the clinical applications of D4 and R4 aptamers in prostate cancer.

Gene-knockout by iSTOP enables rapid reproductive disease modeling and phenotyping in germ cells of the founder generation

Cytosine base editing achieves C•G-to-T•A substitutions and can convert four codons (CAA/CAG/CGA/TGG) into STOP-codons (induction of STOP-codons, iSTOP) to knock out genes with reduced mosaicism. iSTOP enables direct phenotyping in founders' somatic cells, but it remains unknown whether this works in founders' germ cells so as to rapidly reveal novel genes for fertility. Here, we initially establish that iSTOP in mouse zygotes enables functional characterization of known genes in founders' germ cells: Cfap43-iSTOP male founders manifest expected sperm features resembling human "multiple morphological abnormalities of the flagella" syndrome (i.e., MMAF-like features), while oocytes of Zp3-iSTOP female founders have no zona pellucida. We further illustrate iSTOP's utility for dissecting the functions of unknown genes with Ccdc183, observing MMAF-like features and male infertility in Ccdc183-iSTOP founders, phenotypes concordant with those of Ccdc183-KO offspring. We ultimately establish that CCDC183 is essential for sperm morphogenesis through regulating the assembly of outer dynein arms and participating in the intra-flagellar transport. Our study demonstrates iSTOP as an efficient tool for direct reproductive disease modeling and phenotyping in germ cells of the founder generation, and rapidly reveals the essentiality of Ccdc183 in fertility, thus providing a time-saving approach for validating genetic defects (like nonsense mutations) for human infertility.

CCDC146 is required for sperm flagellum biogenesis and male fertility in mice

Multiple morphological abnormalities of the flagella (MMAF) is a severe disease of male infertility, while the pathogenetic mechanisms of MMAF are still incompletely understood. Previously, we found that the deficiency of Ccdc38 might be associated with MMAF. To understand the underlying mechanism of this disease, we identified the potential partner of this protein and found that the coiled-coil domain containing 146 (CCDC146) can interact with CCDC38. It is predominantly expressed in the testes, and the knockout of this gene resulted in complete infertility in male mice but not in females. The knockout of Ccdc146 impaired spermiogenesis, mainly due to flagellum and manchette organization defects, finally led to MMAF-like phenotype. Furthermore, we demonstrated that CCDC146 could interact with both CCDC38 and CCDC42. It also interacts with intraflagellar transport (IFT) complexes IFT88 and IFT20. The knockout of this gene led to the decrease of ODF2, IFT88, and IFT20 protein levels, but did not affect CCDC38, CCDC42, or ODF1 expression. Additionally, we predicted and validated the detailed interactions between CCDC146 and CCDC38 or CCDC42, and built the interaction models at the atomic level. Our results suggest that the testis predominantly expressed gene Ccdc146 is essential for sperm flagellum biogenesis and male fertility, and its mutations might be associated with MMAF in some patients.

Comparative Proteome Analysis of Four Stages of Spermatogenesis in the Small-Spotted Catshark (Scyliorhinus canicula), Using High-Resolution NanoLC-ESI-MS/MS

Spermatogenesis is a highly specialized process of cell proliferation and differentiation leading to the production of spermatozoa from spermatogonial stem cells. Due to its testicular anatomy, Scyliorhinus canicula is an interesting model to explore stage-based changes in proteins during spermatogenesis. The proteomes of four testicular zones corresponding to the germinative niche and to spermatocysts (cysts) with spermatogonia (zone A), cysts with spermatocytes (zone B), cysts with young spermatids (zone C), and cysts with late spermatids (zone D) have been analyzed by nanoLC-ESI-MS/MS. Gene ontology and KEGG annotations were also performed. A total of 3346 multiple protein groups were identified. Zone-specific protein analyses highlighted RNA-processing, chromosome-related processes, cilium organization, and cilium activity in zones A, D, C, and D, respectively. Analyses of proteins with zone-dependent abundance revealed processes related to cellular stress, ubiquitin-dependent degradation by the proteasome, post-transcriptional regulation, and regulation of cellular homeostasis. Our results also suggest that the roles of some proteins, such as ceruloplasmin, optineurin, the pregnancy zone protein, PA28β or the Culling-RING ligase 5 complex, as well as some uncharacterized proteins, during spermatogenesis could be further explored. Finally, the study of this shark species allows one to integrate these data in an evolutionary context of the regulation of spermatogenesis. Mass spectrometry data are freely accessible via iProX-integrated Proteome resources (https://www.iprox.cn/) for reuse purposes.

Genome-Wide Association Studies, Runs of Homozygosity Analysis, and Copy Number Variation Detection to Identify Reproduction-Related Genes in Bama Xiang Pigs

Litter size and teat number are economically important traits in the porcine industry. However, the genetic mechanisms influencing these traits remain unknown. In this study, we analyzed the genetic basis of litter size and teat number in Bama Xiang pigs and evaluated the genomic inbreeding coefficients of this breed. We conducted a genome-wide association study to identify runs of homozygosity (ROH), and copy number variation (CNV) using the novel Illumina PorcineSNP50 BeadChip array in Bama Xiang pigs and annotated the related genes in significant single nucleotide polymorphisms and common copy number variation region (CCNVR). We calculated the ROH-based genomic inbreeding coefficients (FROH) and the Spearman coefficient between FROH and reproduction traits. We completed a mixed linear model association analysis to identify the effect of high-frequency copy number variation (HCNVR; over 5%) on Bama Xiang pig reproductive traits using TASSEL software. Across eight chromosomes, we identified 29 significant single nucleotide polymorphisms, and 12 genes were considered important candidates for litter-size traits based on their vital roles in sperm structure, spermatogenesis, sperm function, ovarian or follicular function, and male/female infertility. We identified 9,322 ROHs; the litter-size traits had a significant negative correlation to FROH. A total of 3,317 CNVs, 24 CCNVR, and 50 HCNVR were identified using cnvPartition and PennCNV. Eleven genes related to reproduction were identified in CCNVRs, including seven genes related to the testis and sperm function in CCNVR1 (chr1 from 311585283 to 315307620). Two candidate genes (NEURL1 and SH3PXD2A) related to reproduction traits were identified in HCNVR34. The result suggests that these genes may improve the litter size of Bama Xiang by marker-assisted selection. However, attention should be paid to deter inbreeding in Bama Xiang pigs to conserve their genetic diversity.

Exome Sequencing Reveals Novel Variants and Expands the Genetic Landscape for Congenital Microcephaly

Congenital microcephaly causes smaller than average head circumference relative to age, sex and ethnicity and is most usually associated with a variety of neurodevelopmental disorders. The underlying etiology is highly heterogeneous and can be either environmental or genetic. Disruption of any one of multiple biological processes, such as those underlying neurogenesis, cell cycle and division, DNA repair or transcription regulation, can result in microcephaly. This etiological heterogeneity manifests in a clinical variability and presents a major diagnostic and therapeutic challenge, leaving an unacceptably large proportion of over half of microcephaly patients without molecular diagnosis. To elucidate the clinical and genetic landscapes of congenital microcephaly, we sequenced the exomes of 191 clinically diagnosed patients with microcephaly as one of the features. We established a molecular basis for microcephaly in 71 patients (37%), and detected novel variants in five high confidence candidate genes previously unassociated with this condition. We report a large number of patients with mutations in tubulin-related genes in our cohort as well as higher incidence of pathogenic mutations in MCPH genes. Our study expands the phenotypic and genetic landscape of microcephaly, facilitating differential clinical diagnoses for disorders associated with most commonly disrupted genes in our cohort.

Identification and characterization of novel proteins associated with CHD4

The CHD (chromodomain helicase DNA binding protein) family consists of nine chromatin remodeling factors that alter chromatin structure in an ATP-dependent manner. CHD4 contributes to the regulation of various cellular activities and processes including development through interaction with multiple proteins including formation of the NuRD (nucleosome remodeling and deacetylase activity) complex. Functions of CHD4 that appear not to be mediated by the NuRD complex or other known interactors have also been identified, however, suggesting the existence of unrecognized proteins that also associate with CHD4. We here generated HeLa-S3 and HEK293T cells with a knock-in allele for FLAG epitope-tagged CHD4 and used these cells to identify proteins that bind to CHD4 with the use of immunoprecipitation followed by liquid chromatography and tandem mass spectrometry. LCORL (ligand-dependent nuclear receptor corepressor like) and NOL4L (nucleolar protein 4 like) were reproducibly identified as novel CHD4 interactors. Furthermore, RNA-sequencing analysis of HEK293T cells depleted of CHD4, LCORL, or NOL4L revealed consistent up-regulation of genes related to the Notch signaling pathway. Our results thus suggest that both LCORL and NOL4L may cooperate with CHD4 to suppress the Notch pathway in mammalian cells.

Flashlight into the Function of Unannotated C11orf52 using Affinity Purification Mass Spectrometry

For an enhanced understanding of the biological mechanisms of human disease, it is essential to investigate protein functions. In a previous study, we developed a prediction method of gene ontology (GO) terms by the I-TASSER/COFACTOR result, and we applied this to uPE1 in chromosome 11. Here, to validate the bioinformatics prediction of C11orf52, we utilized affinity purification and mass spectrometry to identify interacting partners of C11orf52. Using immunoprecipitation methods with three different peptide tags (Myc, Flag, and 2B8) in HEK 293T cell lines, we identified 79 candidate proteins that are expected to interact with C11orf52. The results of a pathway analysis of the GO and STRING database with candidate proteins showed that C11orf52 could be related to signaling receptor binding, cell-cell adhesion, and ribosome biogenesis. Then, we selected three partner candidates of DSG1, JUP, and PTPN11 for verification of the interaction with C11orf52 and confirmed them by colocalization at the cell-cell junctions by coimmunofluorescence experiments. On the basis of this study, we expect that C11orf52 is related to the Wnt signaling pathway via DSG1 from the protein-protein interactions, given the results of a comprehensive analysis of the bioinformatic predictions. The data set is available at the ProteomeXchange consortium via PRIDE repository (PXD026986).

DeepHistoClass: A Novel Strategy for Confident Classification of Immunohistochemistry Images Using Deep Learning

A multitude of efforts worldwide aim to create a single-cell reference map of the human body, for fundamental understanding of human health, molecular medicine, and targeted treatment. Antibody-based proteomics using immunohistochemistry (IHC) has proven to be an excellent technology for integration with large-scale single-cell transcriptomics datasets. The golden standard for evaluation of IHC staining patterns is manual annotation, which is expensive and may lead to subjective errors. Artificial intelligence holds much promise for efficient and accurate pattern recognition, but confidence in prediction needs to be addressed. Here, the aim was to present a reliable and comprehensive framework for automated annotation of IHC images. We developed a multilabel classification of 7848 complex IHC images of human testis corresponding to 2794 unique proteins, generated as part of the Human Protein Atlas (HPA) project. Manual annotation data for eight different cell types was generated as a basis for training and testing a proposed Hybrid Bayesian Neural Network. By combining the deep learning model with a novel uncertainty metric, DeepHistoClass (DHC) Confidence Score, the average diagnostic performance improved from 86.9% to 96.3%. This metric not only reveals which images are reliably classified by the model, but can also be utilized for identification of manual annotation errors. The proposed streamlined workflow can be developed further for other tissue types in health and disease and has important implications for digital pathology initiatives or large-scale protein mapping efforts such as the HPA project.

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A novel method for automated annotation of immunohistochemistry images.

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Introduction of an uncertainty metric, the DeepHistoClass (DHC) confidence score.

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Increased accuracy of automated image predictions.

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Identification of manual annotation errors.

Functionathon: a manual data mining workflow to generate functional hypotheses for uncharacterized human proteins and its application by undergraduate students

About 10% of human proteins have no annotated function in protein knowledge bases. A workflow to generate hypotheses for the function of these uncharacterized proteins has been developed, based on predicted and experimental information on protein properties, interactions, tissular expression, subcellular localization, conservation in other organisms, as well as phenotypic data in mutant model organisms. This workflow has been applied to seven uncharacterized human proteins (C6orf118, C7orf25, CXorf58, RSRP1, SMLR1, TMEM53 and TMEM232) in the frame of a course-based undergraduate research experience named Functionathon organized at the University of Geneva to teach undergraduate students how to use biological databases and bioinformatics tools and interpret the results. C6orf118, CXorf58 and TMEM232 were proposed to be involved in cilia-related functions; TMEM53 and SMLR1 were proposed to be involved in lipid metabolism and C7orf25 and RSRP1 were proposed to be involved in RNA metabolism and gene expression. Experimental strategies to test these hypotheses were also discussed. The results of this manual data mining study may contribute to the project recently launched by the Human Proteome Organization (HUPO) Human Proteome Project aiming to fill gaps in the functional annotation of human proteins. Database URL: http://www.nextprot.org.

GO Enrichment Analysis for Differential Proteomics Using ProteoRE

With the increased simplicity of producing proteomics data, the bottleneck has now shifted to the functional analysis of large lists of proteins to translate this primary level of information into meaningful biological knowledge. Tools implementing such approach are a powerful way to gain biological insights related to their samples, provided that biologists/clinicians have access to computational solutions even when they have little programming experience or bioinformatics support. To achieve this goal, we designed ProteoRE (Proteomics Research Environment), a unified online research service that provides end-users with a set of tools to interpret their proteomics data in a collaborative and reproducible manner. ProteoRE is built upon the Galaxy framework, a workflow system allowing for data and analysis persistence, and providing user interfaces to facilitate the interaction with tools dedicated to the functional and the visual analysis of proteomics datasets. A set of tools relying on computational methods selected for their complementarity in terms of functional analysis was developed and made accessible via the ProteoRE web portal. In this chapter, a step-by-step protocol linking these tools is designed to perform a functional annotation and GO-based enrichment analyses applied to a set of differentially expressed proteins as a use case. Analytical practices, guidelines as well as tips related to this strategy are also provided. Tools, datasets, and results are freely available at http://www.proteore.org , allowing researchers to reuse them.