Identification Of Proteins Research Articles

Genome-wide identification of PAR domain protein 1 (PDP1) targets through ChIP-seq reveals the regulation of diapause-specific characteristics in Culex pipiens.

Insects use seasonal diapause as an alternative strategy to endure adverse seasons. This developmental trajectory is induced by environmental cues like short-day lengths in late summer and early fall, but how insects measure day length is unknown. The circadian clock has been implicated in regulating photoperiodic or seasonal responses in many insects, including the Northern house mosquito, Culex pipiens, which enters adult diapause. To investigate the potential control of diapause by circadian control, we employed ChIP-sequencing to identify the downstream targets of a circadian transcription factor, PAR domain protein 1 (PDP1), that contribute to the hallmark features of diapause. We identified the nearest genes in a 10 kb region of the anticipated PDP1 binding sites, listed prospective targets and searched for PDP1-specific binding sites. By examining the functional relevance to diapause-specific behaviours and modifications such as metabolic pathways, lifespan extension, cell cycle regulation and stress tolerance, eight genes were selected as targets and validated using ChIP-qPCR. In addition, qRT-PCR demonstrated that the mRNA abundance of PDP1 targets increased in the heads of diapausing females during the middle of the scotophase (ZT17) compared with the early photophase (ZT1), in agreement with the peak and trough of PDP1 abundance. Thus, our investigation uncovered the mechanism by which PDP1 might generate a diapause phenotype in insects.

In Vivo Proximity Cross-Linking and Immunoprecipitation of Cell Wall Epitopes Identify Proteins Associated with the Biosynthesis of Matrix Polysaccharides.

Identification of proteins involved in cell wall matrix polysaccharide biosynthesis is crucial to understand plant cell wall biology. We utilized in vivo cross-linking and immunoprecipitation with cell wall antibodies that recognized xyloglucan, xylan, mannan, and homogalacturonan to capture proteins associated with matrix polysaccharides in Arabidopsis protoplasts. The use of cross-linkers allowed us to capture proteins actively associated with cell wall polymers, including those directly interacting with glycans via glycan-protein (GP) cross-linkers and those associated with proteins linked to glycans via a protein-protein (PP) cross-linker. Immunoprecipitations led to the identification of 65 Arabidopsis protein IDs localized in the Golgi, ER, plasma membrane, and others without subcellular localization data. Among these, we found several glycosyltransferases directly involved in polysaccharide synthesis, along with proteins related to cell wall modification and vesicle trafficking. Protein interaction networks from DeepAraPPI and AtMAD databases showed interactions between various IDs, including those related to cell-wall-associated proteins and membrane/vesicle trafficking proteins. Gene expression and coexpression analyses supported the presence and relevance of the proteins to the cell wall processes. Reverse genetic studies using T-DNA insertion mutants of selected proteins revealed changes in cell wall composition and saccharification, further supporting their potential roles in cell wall biosynthesis. Overall, our approach represents a novel approach for studying cell wall polysaccharide biosynthesis and associated proteins, providing advantages over traditional immunoprecipitation techniques. This study provides a list of putative proteins associated with different matrix polysaccharides for further investigation and highlights the complexity of cell wall biosynthesis and trafficking within plant cells.

Recurrent evolution of adhesive defence systems in amphibians by parallel shifts in gene expression

Natural selection can drive organisms to strikingly similar adaptive solutions, but the underlying molecular mechanisms often remain unknown. Several amphibians have independently evolved highly adhesive skin secretions (glues) that support a highly effective antipredator defence mechanism. Here we demonstrate that the glue of the Madagascan tomato frog, Dyscophus guineti, relies on two interacting proteins: a highly derived member of a widespread glycoprotein family and a galectin. Identification of homologous proteins in other amphibians reveals that these proteins attained a function in skin long before glues evolved. Yet, major elevations in their expression, besides structural changes in the glycoprotein (increasing its structural disorder and glycosylation), caused the independent rise of glues in at least two frog lineages. Besides providing a model for the chemical functioning of animal adhesive secretions, our findings highlight how recruiting ancient molecular templates may facilitate the recurrent evolution of functional innovations.

Seasonal Proteome Variations in Orbicella faveolata Reveal Molecular Thermal Stress Adaptations.

Although seasonal water temperatures typically fluctuate by less than 4 °C across most tropical reefs, sustained heat stress with an increase of even 1 °C can alter and destabilize metabolic and physiological coral functions, leading to losses of coral reefs worldwide. The Caribbean region provides a natural experimental design to study how corals respond physiologically throughout the year. While characterized by warm temperatures and precipitation, there is a significant seasonal component with relative cooler and drier conditions during the months of January to February and warmer and wetter conditions during September and October. We conducted a comparative abundance of differentially expressed proteins with two contrasting temperatures during the cold and warm seasons of 2014 and 2015 in Orbicella faveolata, one of the most important and affected reef-building corals of the Caribbean. All presented proteoforms (42) were found to be significant in our proteomics differential expression analysis and classified based on their gene ontology. The results were accomplished by a combination of two-dimensional gel electrophoresis (2DE) to separate and visualize proteins and mass spectrometry (MS) for protein identification. To validate the differentially expressed proteins of Orbicella faveolata at the transcription level, qRT-PCR was performed. Our data indicated that a 3.1 °C increase in temperature in O. faveolata between the cold and warm seasons in San Cristobal and Enrique reefs of southwestern Puerto Rico was enough to affect the expression of a significant number of proteins associated with oxidative and heat stress responses, metabolism, immunity, and apoptosis. This research extends our knowledge into the mechanistic response of O. faveolata to mitigate thermal seasonal temperature variations in coral reefs.

PSPI: A deep learning approach for prokaryotic small protein identification.

Small Proteins (SPs) are pivotal in various cellular functions such as immunity, defense, and communication. Despite their significance, identifying them is still in its infancy. Existing computational tools are tailored to specific eukaryotic species, leaving only a few options for SP identification in prokaryotes. In addition, these existing tools still have suboptimal performance in SP identification. To fill this gap, we introduce PSPI, a deep learning-based approach designed specifically for predicting prokaryotic SPs. We showed that PSPI had a high accuracy in predicting generalized sets of prokaryotic SPs and sets specific to the human metagenome. Compared with three existing tools, PSPI was faster and showed greater precision, sensitivity, and specificity not only for prokaryotic SPs but also for eukaryotic ones. We also observed that the incorporation of (n, k)-mers greatly enhances the performance of PSPI, suggesting that many SPs may contain short linear motifs. The PSPI tool, which is freely available at https://www.cs.ucf.edu/∼xiaoman/tools/PSPI/, will be useful for studying SPs as a tool for identifying prokaryotic SPs and it can be trained to identify other types of SPs as well.

Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows.

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ~3500 proteins at a spatial resolution of 50 µm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.

Mapping and Analysis of Protein and Gene Profile Identification of the Important Role of Transforming Growth Factor Beta in Synovial Invasion in Patients With Pigmented Villonodular Synovitis.

Pigmented villonodular synovitis (PVNS) is a rare benign proliferative disease affecting the soft-tissue lining the synovial joints and tendons. Its etiology is poorly understood, largely limiting the availability of current therapeutic options. Here, we mapped the synovial gene and protein profiles of patients with PVNS, revealed a link between synovial inflammation and invasion, and elucidated the potential molecular mechanism involved. The expression of synovial genes from 6 control individuals, 7 patients with osteoarthritis (OA), and 19 patients with PVNS was analyzed via RNA sequencing. Protein profiles from 5 control individuals, 10 patients with OA, and 32 patients with PVNS were analyzed using label-free proteomics. Microarray and reverse transcription-polymerase chain reaction analyses and immunohistochemical staining were used to evaluate inflammatory cytokine and target gene expression levels in synovial tissue, epithelial cells, and synovial fibroblasts (FLSs) derived from tissue of patients with PVNS. Various signaling pathway inhibitors, small interfering RNAs, and Western blots were used for molecular mechanism studies. Transwell migration and invasion assays were subsequently performed. In total, 522 differentially expressed proteins were identified in the tissues of patients with PVNS. By integrating RNA sequencing and microarray analyses, significant changes in the expression of epithelial-mesenchymal transition (EMT)-related genes, including transforming growth factor TGF-b induced, neural cadherin, epithelial cadherin, SNAIL, and TWIST, were confirmed in the tissue of patients with PVNS compared to the control tissue. In vitro, TGFβ induced EMT and increased epithelial cell migration and invasion. Moreover, TGFβ not only promoted interactions between epithelial cells and FLSs but also directly increased the migration and invasion abilities of FLSs by activating the classical Smad2/3 and nonclassical JNK/AKT signaling pathways. This study provides overall protein and gene profiles of PVNS and identifies the crucial role of TGFβ in synovial invasion pathology. Exploring the related molecular mechanism may also reveal a new strategy or target for PVNS therapy.

Role of circulating inflammatory protein in the development of diabetic renal complications: proteome-wide Mendelian randomization and colocalization analyses.

Diabetes ranks among the most widespread diseases globally, with the kidneys being particularly susceptible to its vascular complications. The identification of proteins for pathogenesis and novel drug targets remains imperative. This study aims to investigate roles of circulating inflammatory proteins in diabetic renal complications. Data on the proteins were derived from a genome-wide protein quantitative trait locus (pQTL) study, while data on diabetic renal complications came from the FinnGen study. In this study, proteome-wide Mendelian randomization (MR) and colocalization analyses were used to assess the relationship between circulating inflammatory proteins and diabetic renal complications. MR approach indicated that elevated levels of interleukin 12B (IL-12B) (OR 1.691, 95%CI 1.179-2.427, P=4.34×10-3) and LIF interleukin 6 family cytokine (LIF) (OR 1.349, 95%CI 1.010-1.801, P=4.23×10-2) increased the risk of type 1 diabetes (T1D) with renal complications, while higher levels of fibroblast growth factor 19 (FGF19) (OR 1.202, 95%CI 1.009-1.432, P=3.93×10-2), fibroblast growth factor 23 (FGF23) (OR 1.379, 95%CI 1.035-1.837, P=2.82×10-2), C-C motif chemokine ligand 7 (CCL7) (OR 1.385, 95%CI 1.111-1.725, P=3.76×10-3), and TNF superfamily member 14 (TNFSF14) (OR 1.244, 95%CI 1.066-1.451, P=5.63×10-3) indicated potential risk factors for type 2 diabetes (T2D) with renal complications. Colocalization analysis supported these findings, revealing that most identified proteins, except for DNER, likely share causal variants with diabetic renal complications. Our study established associations between specific circulating inflammatory proteins and the risk of diabetic renal complications, suggesting these proteins as targets for further investigation into the pathogenesis and potential therapeutic interventions for T1D and T2D with renal complications.

Efficient and rapid digestion of proteins with a dual-enzyme microreactor featuring 3-D pores formed by dopamine/polyethyleneimine/acrylamide-coated KIT-6 molecular sieve

The microreactor with two types of immobilized enzymes, exhibiting excellent orthogonal performance, represents an effective approach to counteract the reduced digestion efficiency resulting from the absence of a single enzyme cleavage site, thereby impacting protein identification. In this study, we developed a hydrophilic dual-enzyme microreactor characterized by rapid mass transfer and superior enzymatic activity. Initially, we selected KIT-6 molecular sieve as the carrier for the dual-IMER due to its three-dimensional network pore structure. Modification involved co-deposition of polyethyleneimine (PEI) and acrylamide (AM) as amine donors, along with dopamine to enhance material hydrophilicity. Remaining amino and double bond functional groups facilitated stepwise immobilization of trypsin and Glu-C. Digestion times for bovine serum albumin (BSA) and bovine hemoglobin (BHb) on the dual-IMER were significantly reduced compared to solution-based digestion (1 min vs. 36 h), resulting in improved sequence coverage (91.30% vs. 82.7% for BSA; 90.24% vs. 89.20% for BHb). Additionally, the dual-IMER demonstrated excellent durability, retaining 96.08% relative activity after 29 reuse cycles. Enhanced protein digestion efficiency can be attributed to several factors: (1) KIT-6’s large specific surface area, enabling higher enzyme loading capacity; (2) Its three-dimensional network pore structure, facilitating faster mass transfer and substance diffusion; (3) Orthogonality of trypsin and Glu-C enzyme cleavage sites; (4) The spatial effect introduced by the chain structure of PEI and glutaraldehyde’s spacing arm, reducing spatial hindrance and enhancing enzyme–substrate interactions; (5) Mild and stable enzyme immobilization. The KIT-6-based dual-IMER offers a promising technical tool for protein digestion, while the PDA/PEI/AM-KIT-6 platform holds potential for immobilizing other proteins or active substances.

Proteomic Identification and Quantification of Basal Endogenous Proteins in the Ileal Digesta of Growing Pigs.

The accurate estimation of basal endogenous losses (BEL) of amino acids at the ileum is indispensable to improve nutrient utilization efficiency. This study used a quantitative proteomic approach to identify variations in BEL in the ileal digesta of growing pigs fed a nitrogen-free diet (NFD) or a casein diet (CAS). Eight barrow pigs (39.8 ± 6.3 kg initial body weight (BW)) were randomly assigned to a 2 × 2 crossover design. A total of 348 proteins were identified and quantified in both treatments, of which 101 showed a significant differential abundance between the treatments (p < 0.05). Functional and pathway enrichment analyses revealed that the endogenous proteins were associated with intestinal metabolic function. Furthermore, differentially abundant proteins (DAPs) in the digesta of pigs fed the NFD enriched terms and pathways that suggest intestinal inflammation, the activation of innate antimicrobial host defense, an increase in cellular autophagy and epithelial turnover, and reduced synthesis of pancreatic and intestinal secretions. These findings suggest that casein diets may provide a more accurate estimation of BEL because they promote normal gastrointestinal secretions. Overall, proteomic and bioinformatic analyses provided valuable insights into the composition of endogenous proteins in the ileal digesta and their relationship with the functions, processes, and pathways modified by diet composition.

Graph-Based Cancer Protein Identification Algorithm Reveals Key Proteins in PPI Networks

Graph-Based Cancer Protein Identification Algorithm Reveals Key Proteins in PPI Networks

Unveiling novel targets in melanoma under melanogenesis stimulation and photodynamic therapy by redox proteomics.

Melanogenesis-stimulated B16-F10 cells enter in a quiescent state, present inhibited mitochondrial respiration and increased reactive oxygen species levels. These alterations suggest that these cells may be under redox signaling, allowing tumor survival. The aim of this study was to evaluate redox-modified proteins in B16-F10 cells after melanogenesis stimulation and rose bengal-photodynamic therapy (RB-PDT). A redox proteomics label-free approach based on the biotin switch assay technique with biotin-HPDP and N-ethylmaleimide was used to assess the thiol-oxidized protein profile. Aconitase was oxidized at Cys-448 and Cys-451, citrate synthase was oxidized at Cys-202 and aspartate aminotransferase (Got2) was oxidized at Cys-272 and Cys-274, exclusively after melanogenesis stimulation. After RB-PDT, only guanine nucleotide-binding protein subunit beta-2-like 1 (Gnb2l1) was oxidized (Cys-168). In contrast, melanogenesis stimulation followed by RB-PDT led to the oxidation of different cysteines in Gnb2l1 (Cys-153 and Cys-249). Besides that, glyceraldehyde-3-phosphate dehydrogenase (Gapdh) presented oxidation at Cys-245, peptidyl-prolyl cis-trans isomerase A (Ppia) was oxidized at Cys-161 and 5,6-dihydroxyindole-2-carboxylic acid oxidase (Tyrp1) was oxidized at Cys-65, Cys-30, and Cys-336 after melanogenesis stimulation followed by RB-PDT. The redox alterations observed in murine melanoma cells and identification of possible target proteins are of great importance to further understand tumor resistance mechanisms.

Advanced Protocol for Molecular Characterization of Viral Genome in Fission Yeast (Schizosaccharomyces pombe).

Fission yeast, a single-cell eukaryotic organism, shares many fundamental cellular processes with higher eukaryotes, including gene transcription and regulation, cell cycle regulation, vesicular transport and membrane trafficking, and cell death resulting from the cellular stress response. As a result, fission yeast has proven to be a versatile model organism for studying human physiology and diseases such as cell cycle dysregulation and cancer, as well as autophagy and neurodegenerative diseases like Alzheimer's, Parkinson's, and Huntington's diseases. Given that viruses are obligate intracellular parasites that rely on host cellular machinery to replicate and produce, fission yeast could serve as a surrogate to identify viral proteins that affect host cellular processes. This approach could facilitate the study of virus-host interactions and help identify potential viral targets for antiviral therapy. Using fission yeast for functional characterization of viral genomes offers several advantages, including a well-characterized and haploid genome, robustness, cost-effectiveness, ease of maintenance, and rapid doubling time. Therefore, fission yeast emerges as a valuable surrogate system for rapid and comprehensive functional characterization of viral proteins, aiding in the identification of therapeutic antiviral targets or viral proteins that impact highly conserved host cellular functions with significant virologic implications. Importantly, this approach has a proven track record of success in studying various human and plant viruses. In this protocol, we present a streamlined and scalable molecular cloning strategy tailored for genome-wide and comprehensive functional characterization of viral proteins in fission yeast.

Protein research in millets: current status and way forward.

Millets' protein studies are lagging behind those of major cereals. Current status and future insights into the investigation of millet proteins are discussed. Millets are important small-seeded cereals majorly grown and consumed by people in Asia and Africa and are considered crops of future food security. Although millets possess excellent climate resilience and nutrient supplementation properties, their research advancements have been lagging behind major cereals. Although considerable genomic resources have been developed in recent years, research on millet proteins and proteomes is currently limited, highlighting a need for further investigation in this area. This review provides the current status of protein research in millets and provides insights to understand protein responses for climate resilience and nutrient supplementation in millets. The reference proteome data is available for sorghum, foxtail millet, and proso millet to date; other millets, such as pearl millet, finger millet, barnyard millet, kodo millet, tef, and browntop millet, do not have any reference proteome data. Many studies were reported on stress-responsive protein identification in foxtail millet, with most studies on the identification of proteins under drought-stress conditions. Pearl millet has a few reports on protein identification under drought and saline stress. Finger millet is the only other millet to have a report on stress-responsive (drought) protein identification in the leaf. For protein localization studies, foxtail millet has a few reports. Sorghum has the highest number of 40 experimentally proven crystal structures, and other millets have fewer or no experimentally proven structures. Further proteomics studies will help dissect the specific proteins involved in climate resilience and nutrient supplementation and aid in breeding better crops to conserve food security.

Large-scale identification of calcium oxalate stone inhibitory proteins in normal human urine

Recent evidence has shown that proteins in normal human urine can inhibit calcium oxalate (CaOx) kidney stone formation. Herein, we performed fast protein liquid chromatography (FPLC) to fractionate normal human urinary proteins using anion-exchange (DEAE) and size-exclusion (Superdex 200) materials. FPLC fractions (F1-F15) were examined by CaOx crystallization, growth, aggregation and crystal-cell adhesion assays. The fractions with potent inhibitory activities against CaOx crystals were then subjected to mass spectrometric protein identification. The data revealed that 13 of 15 fractions showed inhibitory activities in at least one crystal assay. Integrating CaOx inhibitory scores demonstrated that F6, F7 and F8 had the most potent inhibitory activities. NanoLC-ESI-Qq-TOF MS/MS identified 105, 93 and 53 proteins in F6, F7 and F8, respectively. Among them, 60 were found in at least two fractions and/or listed among known inhibitors with solid experimental evidence in the StoneMod database (https://www.stonemod.org). Interestingly, 10 of these 60 potential inhibitors have been reported with lower urinary levels in CaOx stone formers compared with healthy (non-stone) individuals, strengthening their roles as potent CaOx stone inhibitors. Our study provides the largest dataset of potential CaOx stone inhibitory proteins that will be useful for further elucidations of stone-forming mechanisms and ultimately for therapeutic/preventive applications.

Role of actin-binding proteins in cataract formation.

Actin has been implicated in lens opacification; however, the specific actin-related pathways involved in cataracts remain unelucidated. In this study, actin-related proteome changes and signaling pathways involved in the development of cataracts were evaluated. The anterior capsule and phacoemulsification (phaco) cassette contents were collected during cataract surgery from 11 patients with diabetic cataract (DC), 12 patients with age-related cataract (ARC), and seven patients with post-vitrectomy cataract (PVC). Untargeted, global identification and quantification of proteins was performed through liquid chromatography-mass spectrometry with the data-independent acquisition (DIA). In phaco cassette samples, proteins with significantly lower expression in ARC than in DC and PVC were involved in various pathways, including actin binding, actin cytoskeleton reorganization, actin filament capping, cortical actin cytoskeleton organization, and small GTPase-mediated signal transduction pathways. In anterior capsules, proteins with significantly lower expression in ARC than in DC and PVC were involved in actin binding and actin cytoskeleton reorganization pathways. Actin cytoskeleton and actin-binding proteins are involved in lens fiber elongation and differentiation. Rho GTPases contribute to actin cytoskeletal reorganization, and their inactivation is linked to abnormal lens fiber migration. These findings link actin binding to lens fiber integrity, lens opacification, and cataracts.

Homogeneous Ensemble Feature Selection for Mass Spectrometry Data Prediction in Cancer Studies

The identification of important proteins is critical for the medical diagnosis and prognosis of common diseases. Diverse sets of computational tools have been developed for omics data reduction and protein selection. However, standard statistical models with single-feature selection involve the multi-testing burden of low power with limited available samples. Furthermore, high correlations among proteins with high redundancy and moderate effects often lead to unstable selections and cause reproducibility issues. Ensemble feature selection in machine learning (ML) may identify a stable set of disease biomarkers that could improve the prediction performance of subsequent classification models and thereby simplify their interpretability. In this study, we developed a three-stage homogeneous ensemble feature selection (HEFS) approach for both identifying proteins and improving prediction accuracy. This approach was implemented and applied to ovarian cancer proteogenomics datasets comprising (1) binary putative homologous recombination deficiency (HRD)- positive or -negative samples; (2) multiple mRNA classes (differentiated, proliferative, immunoreactive, mesenchymal, and unknown samples). We conducted and compared various ML methods with HEFS including random forest (RF), support vector machine (SVM), and neural network (NN) for predicting both binary and multiple-class outcomes. The results indicated that the prediction accuracies varied for both binary and multiple-class classifications using various ML approaches with the proposed HEFS method. RF and NN provided better prediction accuracies than simple Naive Bayes or logistic models. For binary outcomes, with a sample size of 122 and nine selected prediction proteins using our proposed three-stage HEFS approach, the best ensemble ML (Treebag) achieved 83% accuracy, 85% sensitivity, and 81% specificity. For multiple (five)-class outcomes, the proposed HEFS-selected proteins combined with Principal Component Analysis (PCA) in NN resulted in prediction accuracies for multiple-class classifications ranging from 75% to 96% for each of the five classes. Despite the different prediction accuracies of the various models, HEFS identified consistent sets of proteins linked to the binary and multiple-class outcomes.

P-085 Transcriptomic and proteomic characterization of unexplained male infertility: alterations in energy metabolism

Abstract Study question Which are the transcriptomic and proteomic profiles of spermatozoa belonging to patients with Unexplained Male Infertility (UMI)? Summary answer Transcriptomic and proteomic profiles of UMI patients differ from the fertile men, having the energy metabolism altered. What is known already About 30% of infertile couples suffer from “Unexplained Infertility” (UI). Considering that the male factor contributes to 50% of infertility cases, it is estimated that half of all couple UI cases are due to unexplained male infertility (UMI). Men are diagnosed with UMI when despite having “normal” seminal parameters they are unable to conceive. Due to the lack of UMI classification criteria and the seminogram-only-based infertility diagnosis, little is known about the mechanisms underlying UMI. Study design, size, duration 80 normozoospermic human semen samples with proven fertility and 80 samples from patients with UMI were used for this study. Ejaculates were obtained from Clínica Quirón Bilbao between 2012 and 2018, and after capacitation they were pooled to perform protein and RNA extractions. Participants/materials, setting, methods For transcriptomic analysis, libraries were prepared using the SMARTer Stranded Total RNA-Seq Kit v3. Sequencing was performed on NextSeq 2000 system (1x 50 bp, 50 cycles, P3 kit) at Centre de Regulació Genómica (CRG). For the proteomic analysis, Tandem MassTag (TMT) 6-plex isotopic labeling strategy was adopted, and generated peptides were run in a Q Exactive mass spectrometer. To find differentially expressed genes and proteins between both groups EdgeR and Perseus softwares were employed. Main results and the role of chance In the present study, a total of 156.124 transcripts and 1722 proteins were identified in human sperm. Principal Component Analysis (PCA) confirmed the existence of distinguishable differences in the transcriptomic and proteomic profile of control and UMI samples. Specifically, 3112 differentially expressed transcripts and 385 differentially expressed proteins were identified. Among the differentially expressed proteins, 49 were correlated with RNA expression. Coherent RNA-protein signatures were mainly related to axonemal dynein complex assembly and flagellated sperm motility. Proteins involved in energy metabolism were enriched in UMI protein signatures but were not well correlated with the RNA. Furthermore, genes involved in protein transport and chromosome condensation were highly enriched in UMI group but were not detected by proteomics profiling. According to our results, there is a lack of RNA-protein correlation at human sperm. However, differential transcriptomic and proteomic profiles were found when comparing fertile normozoospermic samples to UMI samples. Concretely, our results suggest that altered energy metabolism may be one of the key factors in patients leading with UMI. Thus, the study of human sperm metabolism may be essential to find new targets of male infertility. Limitations, reasons for caution The lack of a consensus on the classification criteria of UMI makes this group of patients very heterogeneous. Further studies are needed to identify and validate specific transcripts and/or proteins that may alter specific metabolic processes and cause infertility. Wider implications of the findings The study of human sperm metabolism may be essential to understand the causes of many UMI cases. In this context, the identification of key protein or transcripts could be very helpful to predict the success of the assisted reproductive treatments. Trial registration number Not applicable

P-095 Towards deciphering the molecular architecture of the human sperm connecting piece

Abstract Study question How can we make the human sperm connecting piece accessible for structural analysis by cryo-electron tomography (cryo-ET)? Summary answer Preparation of sperm by chemical thinning or production of lamellae via cryo-focused ion beam (cryo-FIB) milling allows direct imaging of the human sperm connecting piece. What is known already Previous studies from our group and others have demonstrated the versatility of cryo-ET to advance our understanding of sperm biology. Structures of macromolecular complexes have been resolved in vitro and in situ, enabling a functional assessment at molecular or even atomic level. Resolving structures at high resolution further allowed identification of proteins previously not known to have a role in mediating male fertility. Such insights are instrumental to further improve diagnosis and treatment of male infertility. Study design, size, duration In our research study we use sperm samples from patients undergoing IVF treatment or donor material, which we receive through an ongoing collaboration with the Division of Woman and Baby, University Medical Centre Utrecht (UMCU). These samples are processed in our own laboratory and subsequently imaged by cryo-ET at the Electron Microscopy Centre of Utrecht University. Participants/materials, setting, methods Due to its thickness, the connecting piece cannot be directly analyzed by cryo-ET. Thus, we designed two strategies to achieve thinning of this area and allow collection of tomograms for structural analysis. While the first approach involves incubation of sperm with a detergent, a reducing agent and heparin, the second approach utilizes cryo-FIB milling to produce thin lamellae of the connecting piece. Main results and the role of chance Both strategies developed to access the connecting piece with cryo-ET are effective and allowed us a glimpse of the molecular landscape of the link between sperm head and tail. Chemical thinning of the connecting piece enabled imaging of the proximal and distal centriole while still embedded in the segmented columns or outer dense fibers, respectively. Furthermore, electron density within the microtubules of both centrioles indicates that they are decorated by microtubule inner proteins. Data obtained from lamellae produced by cryo-FIB milling complements these findings, displaying regular densities along the microtubules extending from the proximal centriole. Analyzing tomograms collected from cryo-FIB lamellae we further found a regular protein density that appears to be connecting the nuclear envelope to the base plate. Moreover, cryo-ET of lamellae allowed a detailed view of nuclear pore complexes and the postacrosomal sheath in their native environment. Limitations, reasons for caution Altering the native state of the sperm cell by chemical preparation is a limitation of this approach. Cryo-FIB milling retains the native state of the cell but is limited in throughput. To improve our cryo-FIB milling approach, we will implement automated milling procedures. Wider implications of the findings Chemical preparation and cryo-FIB milling of sperm enable the in-depth analysis of the connecting piece by cryo-ET. These strategies can now be applied to provide structural details at the molecular level and thus advance our understanding of male infertility related to defects of the head-tail junction. Trial registration number not applicable

Effect of dynamic exclusion and the use of FAIMS, DIA and MALDI-mass spectrometry imaging with ion mobility on amyloid protein identification

Amyloidosis is a disease characterized by local and systemic extracellular deposition of amyloid protein fibrils where its excessive accumulation in tissues and resistance to degradation can lead to organ failure. Diagnosis is challenging because of approximately 36 different amyloid protein subtypes. Imaging methods like immunohistochemistry and the use of Congo red staining of amyloid proteins for laser capture microdissection combined with liquid chromatography tandem mass spectrometry (LMD/LC–MS/MS) are two diagnostic methods currently used depending on the expertise of the pathology laboratory. Here, we demonstrate a streamlined in situ amyloid peptide spatial mapping by Matrix Assisted Laser Desorption Ionization–Mass Spectrometry Imaging (MALDI-MSI) combined with Trapped Ion Mobility Spectrometry for potential transthyretin (ATTR) amyloidosis subtyping. While we utilized the standard LMD/LC–MS/MS workflow for amyloid subtyping of 31 specimens from different organs, we also evaluated the potential introduction in the MS workflow variations in data acquisition parameters like dynamic exclusion, or testing Data Dependent Acquisition combined with High-Field Asymmetric Waveform Ion Mobility Spectrometry (DDA FAIMS) versus Data Independent Acquisition (DIA) for enhanced amyloid protein identification at shorter acquisition times. We also demonstrate the use of Mascot’s Error Tolerant Search and PEAKS de novo sequencing for the sequence variant analysis of amyloidosis specimens.