High-throughput mass spectrometric discovery of protein post-translational modifications

Expression and basic biochemical characteristics of recombinant surfactant protein D of bottlenose dolphin (Tursiopstruncatus)

We previously identified surfactant protein D (SP-D) in the bottlenose dolphin Tursiops truncatus as a unique evolutionary factor of the cetacean pulmonary immune system. In this short report, recombinant SP-D of bottlenose dolphin (dSP-D) was synthesized in mammalian cells, and its properties were analyzed in vitro. The recombinant proteins were purified using Ni-carrier or Co-carrier. Sodium dodecyl sulfate poly-acrylamide gel electrophoresis and western blotting revealed a 50 kDa major band with minor secondary bands. Enzyme-linked immunosorbent assay-like methods revealed that recombinant dSP-D bonded to gram-positive and gram-negative bacterial walls. Our findings suggest the clinical usefulness of dSP-D for cetacean pneumonia.

Analysis of Auxin-Encoding Gene Family in Vigna radiata and It's Cross-Species Expression Modulating Waterlogging Tolerance in Wild Vigna umbellata

Mungbean is known to be susceptible to waterlogging (WL) stress. Some of the wild species have the potential to tolerate this through various physiological and molecular mechanisms. Auxin Response Factor (ARF) and Auxin/Indole Acetic Acid (AUX/IAA), an early responsive gene family, has multiple functions in growth, development, and stress tolerance. Here, we report the first comprehensive analysis of the ARF and AUX/IAA gene family in mungbean. A total of 26 ARF and 19 AUX/IAA genes were identified from the mungbean genome. The ARF and AUX/IAA candidates were clearly grouped into two major clades. Further, the subgrouping within the major clades indicated the presence of significant diversity. The gene structure, motif analysis, and protein characterization provided the clue for further fundamental research. Out of the10 selected candidate genes, VrARF-5, VrARF-11, VrARF-25, and VrAUX/IAA-9 were found to significantly multiple-fold gene expression in the hypocotyl region of WL-tolerant wild relatives (PRR 2008-2) provides new insight into a role in the induction of lateral root formation under WL stress. The analysis provides an insight into the structural diversity of ARF and AUX/IAA genes in mungbean. These results increase our understanding of ARF and AUX/IAA genes and therefore offer robust information for functional investigations, which can be taken up in the future and will form a foundation for improving tolerance against waterlogging stress.

Kalium 3.0 is a comprehensive depository of natural, artificial, and labeled polypeptides acting on potassium channels

Here, we introduce the third release of Kalium database (http://kaliumdb.org/), a manually curated comprehensive depository that accumulates data on polypeptide ligands of potassium channels. The major goal of this amplitudinous update is to summarize findings for natural polypeptide ligands of K+ channels, as well as data for the artificial derivatives of these substances obtained over the decades of exploration. We manually analyzed more than 700 original manuscripts and systematized the information on mutagenesis, production of radio- and fluorescently labeled derivatives, and the molecular pharmacology of K+ channel ligands. As a result, data on more than 1200 substances were processed and added enriching the database content fivefold. We also included the electrophysiological data obtained on the understudied and neglected K+ channels including the heteromeric and concatenated channels. We associated target channels in Kalium with corresponding entries in the official database of the International Union of Basic and Clinical Pharmacology. Kalium was supplemented with an adaptive Statistics page, where users are able to obtain actual data output. Several other improvements were introduced, such as a color code to distinguish the range of ligand activity concentrations and advanced tools for filtration and sorting. Kalium is a fully open-access database, crosslinked to other databases of interest. It can be utilized as a convenient resource containing ample up-to-date information about polypeptide ligands of K+ channels.

Advances in Mass Spectrometry-Based Single Cell Analysis

Technological developments and improvements in single-cell isolation and analytical platforms allow for advanced molecular profiling at the single-cell level, which reveals cell-to-cell variation within the admixture cells in complex biological or clinical systems. This helps to understand the cellular heterogeneity of normal or diseased tissues and organs. However, most studies focused on the analysis of nucleic acids (e.g., DNA and RNA) and mass spectrometry (MS)-based analysis for proteins and metabolites of a single cell lagged until recently. Undoubtedly, MS-based single-cell analysis will provide a deeper insight into cellular mechanisms related to health and disease. This review summarizes recent advances in MS-based single-cell analysis methods and their applications in biology and medicine.

Diversity and prevalence of type VI secretion system effectors in clinical Pseudomonas aeruginosa isolates

Pseudomonas aeruginosa is an opportunistic pathogen and a major driver of morbidity and mortality in people with Cystic Fibrosis (CF). The Type VI secretion system (T6SS) is a molecular nanomachine that translocates effectors across the bacterial membrane into target cells or the extracellular environment enabling intermicrobial interaction. P. aeruginosa encodes three T6SS clusters, the H1-, H2- and H3-T6SS, and numerous orphan islands. Genetic diversity of T6SS-associated effectors in P. aeruginosa has been noted in reference strains but has yet to be explored in clinical isolates. Here, we perform a comprehensive bioinformatic analysis of the pangenome and T6SS effector genes in 52 high-quality clinical P. aeruginosa genomes isolated from CF patients and housed in the Personalised Approach to P. aeruginosa strain repository. We confirm that the clinical CF isolate pangenome is open and principally made up of accessory and unique genes that may provide strain-specific advantages. We observed genetic variability in some effector/immunity encoding genes and show that several well-characterised vgrG and PAAR islands are absent from numerous isolates. Our analysis shows clear evidence of disruption to T6SS genomic loci through transposon, prophage, and mobile genetic element insertions. We identified an orphan vgrG island in P. aeruginosa strain PAK and five clinical isolates using in silico analysis which we denote vgrG7, predicting a gene within this cluster to encode a Tle2 lipase family effector. Close comparison of T6SS loci in clinical isolates compared to reference P. aeruginosa strain PAO1 revealed the presence of genes encoding eight new T6SS effectors with the following putative functions: cytidine deaminase, lipase, metallopeptidase, NADase, and pyocin. Finally, the prevalence of characterised and putative T6SS effectors were assessed in 532 publicly available P. aeruginosa genomes, which suggests the existence of accessory effectors. Our in silico study of the P. aeruginosa T6SS exposes a level of genetic diversity at T6SS genomic loci not seen to date within P. aeruginosa, particularly in CF isolates. As understanding the effector repertoire is key to identifying the targets of T6SSs and its efficacy, this comprehensive analysis provides a path for future experimental characterisation of these mediators of intermicrobial competition and host manipulation.

CNNArginineMe: A CNN structure for training models for predicting arginine methylation sites based on the One-Hot encoding of peptide sequence

Protein arginine methylation (PRme), as one post-translational modification, plays a critical role in numerous cellular processes and regulates critical cellular functions. Though several in silico models for predicting PRme sites have been reported, new models may be required to develop due to the significant increase of identified PRme sites. In this study, we constructed multiple machine-learning and deep-learning models. The deep-learning model CNN combined with the One-Hot coding showed the best performance, dubbed CNNArginineMe. CNNArginineMe performed best in AUC scoring metrics in comparisons with several reported predictors. Additionally, we employed CNNArginineMe to predict arginine methylation proteome and performed functional analysis. The arginine methylated proteome is significantly enriched in the amyotrophic lateral sclerosis (ALS) pathway. CNNArginineMe is freely available at https://github.com/guoyangzou/CNNArginineMe.

Understanding the catalytic abilities of class IV sirtuin OsSRT1 and its linkage to the DNA repair system under stress conditions

The roles of sirtuins in plants are slowly unraveling. Regarding OsSRT1, there are only reports of its H3K9Ac deacetylation. Here we detect the other lysine deacetylation sites in histones, H3 and H4. Further, our studies shed light on its dual enzyme capability with preference for mono ADP ribosylation over deacetylation. OsSRT1 can specifically transfer the single ADP ribose group on its substrates in an enzymatic manner. This mono ADPr effect is not well known in plants, more so for deacetylases. The products of this reaction (NAM and ADP ribose) have a negative effect on this enzyme's action suggesting a tighter regulation. Resveratrol, a natural plant polyphenol proves to be a good activator of this enzyme at 150 ± 40 µM concentration. Under different abiotic stress conditions, we could link this ADP ribosylase activity to the DNA damage repair (DDR) pathway by activating the enzyme PARP1. There is also evidence of OsSRT1's interaction with the components of DDR machinery. Changes in the extent of different histone deacetylation by OsSRT1 is also related with these stress conditions. Metal stress in plants also influences these enzyme activities. Structurally there is a long C-terminal domain in OsSRT1 in comparison to other classes of plant sirtuins, which is required for its catalysis.

Myoglobin from Atlantic and Tinker mackerels: Purification, characterization and its possible use as a molecular marker

Here, we report the characterization (purification, autoxidation rate, pseudoperoxidase activity) and amino acid sequence determination of S. scombrus (Atlantic mackerel) and S. colias (Tinker mackerel) mioglobins (Mbs), considering the increasing consumption of fresh and canned mackerel meat and Mb implication in meat storage (e.g.: browning and lipid oxidation). We found that Atlantic mackerel Mb has major autoxidation rate (0.204 ± 0.013 h^-1) compared to Tinker mackerel Mb (0.140 ± 0.009 h^-1), while the pseudoperoxidase activity is major for Tinker mackerel (K_m: 87.71 ± 7.19 μM; k_cat: 0.32 s^-1) Mb with respect to Atlantic mackerel (K_m: 96.08 ± 6.91 μM; k_cat: 0.50 s^-1). These functional differences are confirmed by primary structure determination, in which six amino acid substitutions are found, with the first N-terminal amino acid residue acetylated. Furthermore, we predicted by AphaFold 3D model both fish Mbs and used them to investigate the possible structural differences. In addition, phylogenetic analysis using Mb sequences from Scombridae family confirms that Atlantic and Tinker mackerels are two distinct species. Finally, an analytic qualitative RP-HPLC method to distinguish S. scombrus and S. colias specimens was developed considering the different retention times of the two mackerel apoMbs.

Unraveling post-translational modifications in Echinococcus granulosus sensu lato

Echinococcus granulosus sensu lato (s.l.) is the helminth parasite responsible for cystic echinococcosis, a neglected tropical disease currently affecting millions of people worldwide. Incomplete knowledge on the parasite biochemistry contributes, at least partially, to the limited development of useful biotechnological advances for the infection control. In this sense, little information is available regarding post-translational modifications (PTMs) occurring in E. granulosus s.l. proteins, which ultimately may affect the performance of biotechnological products to be developed. Therefore, we report here a proteomic analysis of the parasite PTMs identified through FindMod software applied to a set of tegumental proteins previously characterized by mass spectrometry (MALDI-TOF/TOF) analysis of protein spots from a 2D electrophoresis gel. Manual searches for already annotated proteins exhibiting such PTMs were also performed within proteome databases of E. granulosus s.l. and other platyhelminthes. In addition, key enzymes involved in PTMs modifications were searched for within E. granulosus s.l. proteome. Finally, the presence of selected PTMs was further confirmed by a high-resolution proteomic approach (nanoLC-MS/MS). A set of 22 different PTMs most likely to be present in the parasite was suggested, 9 of them with high confidence as they were identified in the same m/z fragment by both proteomic techniques (acetylation, deamidation, deamidation followed by methylation, mono- and di-hydroxylation, mono- and di-methylation, S-nitrosylation and phosphorylation). Interestingly, 5 PTMs were herein identified for the first time in E. granulosus s.l. proteins. Our results expand the scarcely studied topic of PTMs in platyhelminthes.

Novel Post-translational Modifications in Human Serum Albumin

Aim:

This study aims to identify novel post-translational modifications in human serum albumin by mass spectrometry.

Background:

Serum albumin is the most abundant protein in plasma, has many physiological functions, and is in contact with most of the cells and tissues of the human body. Post-translational modifications (PTMs) may affect functions, stability, and localization of albumin.

Objective:

Identify novel PTMs in human serum albumin by mass spectrometry.

Methods:

Human serum albumin (HSA) was used for tryptic digestion in-solution or in-gel. Mass spectrometry was applied to identify PTMs in HSA. 3-dimensional modeling was applied to explore the potential impact of PTMs on known functions of albumin.

Results:

Here, we report the identification of 61 novel PTMs of human serum albumin. Phosphorylation, glycosylation, nitrosylation, deamidation, methylation, acetylation, palmitoylation, geranylation, and farnesylation are some examples of the identified PTMs. Mass spectrometry was used for the identification of PTMs in a purified HSA and HSA from the human plasma. Threedimensional modeling of albumin with selected PTMs showed the location of these PTMs in the regions involved in albumin interactions with drugs, metals, and fatty acids. The location of PTMs in these regions may modify the binding capacity of albumin.

Conclusion:

This report adds 61 novel PTMs to the catalog of human albumin.

Current status of PTMs structural databases: applications, limitations and prospects

Protein 3D structures, determined by their amino acid sequences, are the support of major crucial biological functions. Post-translational modifications (PTMs) play an essential role in regulating these functions by altering the physicochemical properties of proteins. By virtue of their importance, several PTM databases have been developed and released in decades, but very few of these databases incorporate real 3D structural data. Since PTMs influence the function of the protein and their aberrant states are frequently implicated in human diseases, providing structural insights to understand the influence and dynamics of PTMs is crucial for unraveling the underlying processes. This review is dedicated to the current status of databases providing 3D structural data on PTM sites in proteins. Some of these databases are general, covering multiple types of PTMs in different organisms, while others are specific to one particular type of PTM, class of proteins or organism. The importance of these databases is illustrated with two major types of in silico applications: predicting PTM sites in proteins using machine learning approaches and investigating protein structure-function relationships involving PTMs. Finally, these databases suffer from multiple problems and care must be taken when analyzing the PTMs data.

Flavonoid 3'-hydroxylase of Camellia nitidissima Chi. promotes the synthesis of polyphenols better than flavonoids

Camellia nitidissima Chi. is an ornamental plant of the genus Camellia L. Its flowers contain a lot of flavonoids and polyphenols. Flavonoid 3'-hydroxylase (F3'H) plays an important role in the synthesis of flavonoids, polyphenols and anthocyanins. We used PCR amplification, quantitative PCR, High-performance liquid chromatography, subcellular localization, and agrobacterium-mediated leaf disk method to study the the function of CnF3'H. The full length of CnF3'H was 1859 bp (GenBank code: HQ290518.1), with an open reading frame of 1577 bp, and encoded 518 amino acid. A phylogenetic tree analysis showed that CnF3'H was closely related to Camellia sinensis L. and C. sinensis cultivar Zhonghuang. CnF3'H was expressed in flowers, leaves, fruits, sepals, petals and stamens of C. nitidissima, and during the flowering process the expression level in flower decreased initially and then increased. CnF3'H expression was significantly positive correlated with polyphenol contents in C. nitidissima. A CnF3'H-EGFP expression vector was constructed to do the subcellular localization, we found that CnF3'H was obviously localized in the nuclear envelope and cytomembrane. In transgenic tobacco flowers, the total polyphenol content and various polyphenol constituents were significantly increased with high CnF3'H expression level, while total flavonoid contents and some flavonol constituents were increased slightly. These findings suggest that CnF3'H promotes the synthesis of polyphenols better than flavonoids.

Proteome analysis using machine learning approaches and its applications to diseases

With the tremendous developments in the fields of biological and medical technologies, huge amounts of data are generated in the form of genomic data, images in medical databases or as data on protein sequences, and so on. Analyzing this data through different tools sheds light on the particulars of the disease and our body's reactions to it, thus, aiding our understanding of the human health. Most useful of these tools is artificial intelligence and deep learning (DL). The artificially created neural networks in DL algorithms help extract viable data from the datasets, and further, to recognize patters in these complex datasets. Therefore, as a part of machine learning, DL helps us face all the various challenges that come forth during protein prediction, protein identification and their quantification. Proteomics is the study of such proteins, their structures, features, properties and so on. As a form of data science, Proteomics has helped us progress excellently in the field of genomics technologies. One of the major techniques used in proteomics studies is mass spectrometry (MS). However, MS is efficient with analysis of large datasets only with the added help of informatics approaches for data analysis and interpretation; these mainly include machine learning and deep learning algorithms. In this chapter, we will discuss in detail the applications of deep learning and various algorithms of machine learning in proteomics.

Human growth hormone proteoform pattern changes in pituitary adenomas: Potential biomarkers for 3P medical approaches

Relevance

Human growth hormone (hGH) is synthesized, stored, and secreted by somatotroph cells in the pituitary gland, and promotes human growth and metabolism. Compared to a normal pituitary, a GH-secreting pituitary adenoma can secrete excessive GH to cause pathological changes in body tissues. GH proteoform changes would be associated with GH-related disease pathogenesis.

Purpose

This study aimed to elucidate changes in GH proteoforms between GH-secreting pituitary adenomas and control pituitaries for the predictive diagnostics, targeted prevention, and personalization of medical services.

Methods

The isoelectric point (pI) and relative molecular mass (Mr) are two basic features of a proteoform that can be used to effectively array and detect proteoforms with two-dimensional gel electrophoresis (2DGE) and 2DGE-based western blot. GH proteoforms were characterized with liquid chromatography (LC) and mass spectrometry (MS). Phosphoproteomics, ubiquitinomics, acetylomics, and bioinformatics were used to analyze post-translational modifications (PTMs) of GH proteoforms in GH-secreting pituitary adenoma tissues and control pituitaries.

Results

Sixty-six 2D gel spots were found to contain hGH, including 46 spots (46 GH proteoforms) in GH-secreting pituitary adenomas and 35 spots (35 GH proteoforms) in control pituitaries. Further, 35 GH proteoforms in control pituitary tissues were matched with 35 of 46 GH proteoforms in GH-secreting pituitary adenoma tissues; and 11 GH proteoforms were presented in only GH-secreting pituitary adenoma tissues but not in control pituitary tissues. The matched 35 GH proteoforms showed quantitative changes in GH-secreting pituitary adenomas compared to the controls. The quantitative levels of those 46 GH proteoforms in GH-secreting pituitary adenomas were significantly different from those 35 GH proteoforms in control pituitaries. Meanwhile, different types of PTMs were identified among those GH proteoforms. Phosphoproteomics identified phosphorylation at residues Ser77, Ser132, Ser134, Thr174, and Ser176 in hGH. Ubiquitinomics identified ubiquitination at residue Lys96 in hGH. Acetylomics identified acetylation at reside Lys171 in hGH. Deamination was identified at residue Asn178 in hGH.

Conclusion

These findings provide the first hGH proteoform pattern changes in GH-secreting pituitary adenoma tissues compared to control pituitary tissues, and the status of partial PTMs in hGH proteoforms. Those data provide in-depth insights into biological roles of hGH in GH-related diseases, and identify hGH proteoform pattern biomarkers for treatment of a GH-secreting pituitary adenoma in the context of 3P medicine -predictive diagnostics, targeted prevention, and personalization of medical services.

Supplementary information

The online version contains supplementary material available at 10.1007/s13167-021-00232-7.

Functional Diversification of the Dihydroflavonol 4-Reductase from Camellia nitidissima Chi. in the Control of Polyphenol Biosynthesis

Plant secondary metabolism is complex in its diverse chemical composition and dynamic regulation of biosynthesis. How the functional diversification of enzymes contributes to the diversity is largely unknown. In the flavonoids pathway, dihydroflavonol 4-reductase (DFR) is a key enzyme mediating dihydroflavanol into anthocyanins biosynthesis. Here, the DFR homolog was identified from Camellia nitidissima Chi. (CnDFR) which is a unique species of the genus Camellia with golden yellow petals. Sequence analysis showed that CnDFR possessed not only conserved catalytic domains, but also some amino acids peculiar to Camellia species. Gene expression analysis revealed that CnDFR was expressed in all tissues and the expression of CnDFR was positively correlated with polyphenols but negatively with yellow coloration. The subcellular localization of CnDFR by the tobacco infiltration assay showed a likely dual localization in the nucleus and cell membrane. Furthermore, overexpression transgenic lines were generated in tobacco to understand the molecular function of CnDFR. The analyses of metabolites suggested that ectopic expression of CnDFR enhanced the biosynthesis of polyphenols, while no accumulation of anthocyanins was detected. These results indicate a functional diversification of the reductase activities in Camellia plants and provide molecular insights into the regulation of floral color.

Lactoferrin-Derived Peptide Lactofungin Is Potently Synergistic with Amphotericin B

Lactoferrin (LF) is an iron-binding glycoprotein with broad-spectrum antimicrobial activity. Previously, we discovered that LF synergistically enhanced the antifungal efficacy of amphotericin B (AMB) across a variety of yeast species and subsequently hypothesized that this synergy was enhanced by the presence of small peptides derived from the whole LF molecule. In this study, LF was digested with pepsin under a range of conditions. The resulting hydrolysates exhibited enhanced synergy with AMB compared to its synergy with undigested LF. Samples were analyzed using matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry, and 14 peptides were identified. The sequences of these peptides were predicted by matching their molecular weights to those of a virtual digest with pepsin. The relative intensities of predicted peptides in each hydrolysate were compared with the activity of the hydrolysate, and the structural and physicochemical properties of the peptides were assessed. From this, a 30-residue peptide was selected for synthesis and dubbed lactofungin (LFG). Pure LFG was highly synergistic with AMB, outperforming native LF in all fungal species tested. With potential for further structural and chemical improvements, LFG is an excellent lead for development as an antifungal adjuvant.

Novel serine/threonine-O-glycosylation with N-acetylneuraminic acid and 3-deoxy-D-manno-octulosonic acid by bacterial flagellin glycosyltransferases

Some bacterial flagellins are O-glycosylated on surface-exposed serine/threonine residues with nonulosonic acids such as pseudaminic acid, legionaminic acid and their derivatives by flagellin nonulosonic acid glycosyltransferases, also called motility-associated factors (Maf). We report here two new glycosidic linkages previously unknown in any organism, serine/threonine-O-linked N-acetylneuraminic acid (Ser/Thr-O-Neu5Ac) and serine/threonine-O-linked 3-deoxy-D-manno-octulosonic acid or keto-deoxyoctulosonate (Ser/Thr-O-KDO), both catalyzed by Geobacillus kaustophilus Maf and Clostridium botulinum Maf. We identified these novel glycosidic linkages in recombinant G. kaustophilus and C. botulinum flagellins that were coexpressed with their cognate recombinant Maf protein in Escherichia coli strains producing the appropriate nucleotide sugar glycosyl donor. Our finding that both G. kaustophilus Maf (putative flagellin sialyltransferase) and C. botulinum Maf (putative flagellin legionaminic acid transferase) catalyzed Neu5Ac and KDO transfer on to flagellin indicates that Maf glycosyltransferases display donor substrate promiscuity. Maf glycosyltransferases have the potential to radically expand the scope of neoglycopeptide synthesis and posttranslational protein engineering.

Chemical Probes Reveal Sirt2's New Function as a Robust "Eraser" of Lysine Lipoylation

Lysine lipoylation, a highly conserved lysine post-translational modification, plays a critical role in regulating cell metabolism. The catalytic activity of a number of vital metabolic proteins, such as pyruvate dehydrogenase (PDH), depends on lysine lipoylation. Despite its important roles, the detailed biological regulatory mechanism of lysine lipoylation remains largely unexplored. Herein we designed a powerful affinity-based probe, KPlip, to interrogate the interactions of lipoylated peptide/proteins under native cellular environment. Large-scale chemical proteomics analysis revealed a number of binding proteins of KPlip, including sirtuin 2 (Sirt2), an NAD⁺-dependent protein deacylase. To explore the potential activity of Sirt2 toward lysine lipoylation, we designed a single-step fluorogenic probe, KTlip, which reports delipoylation activity in a continuous manner. The results showed that Sirt2 led to significant delipoylation of KTlip, displaying up to a 60-fold fluorescence increase in the assay. Further kinetic experiments with different peptide substrates revealed that Sirt2 can catalyze the delipoylation of peptide (DLAT-PDH, K259) with a remarkable catalytic efficiency (k_cat/K_m) of 3.26 × 10³ s^-1 M^-1. The activity is about 400-fold higher than that of Sirt4, the only mammalian enzyme with known delipoylation activity. Furthermore, overexpression and silencing experiments demonstrated that Sirt2 regulates the lipoylation level and the activity of endogenous PDH, thus unequivocally confirming that PDH is a genuine physiological substrate of Sirt2. Using our chemical probes, we have successfully established the relationship between Sirt2 and lysine lipoylation in living cells for the first time. We envision that such chemical probes will serve as useful tools for delineating the roles of lysine lipoylation in biology and diseases.

Kalium 2.0, a comprehensive database of polypeptide ligands of potassium channels

Potassium channels are the most diverse group of ion channels in humans. They take vital parts in numerous physiological processes and their malfunction gives rise to a range of pathologies. In addition to small molecules, there is a wide selection of several hundred polypeptide ligands binding to potassium channels, the majority of which have been isolated from animal venoms. Until recently, only scorpion toxins received focused attention being systematically assembled in the manually curated Kalium database, but there is a diversity of well-characterized potassium channel ligands originating from other sources. To address this issue, here we present the updated and improved Kalium 2.0 that covers virtually all known polypeptide ligands of potassium channels and reviews all available pharmacological data. In addition to an expansion, we have introduced several new features to the database including posttranslational modification annotation, indication of ligand mode of action, BLAST search, and possibility of data export.

Proteomics: Clinical and research applications in respiratory diseases

The proteome is the study of the protein content of a definable component of an organism in biology. However, the tissue-specific expression of proteins and the varied post-translational modifications, splice variants and protein-protein complexes that may form, make the study of protein a challenging yet vital tool in answering many of the unanswered questions in medicine and biology to date. Indeed, the spatial, temporal and functional composition of proteins in the human body has proven difficult to elucidate for many years. Given the effect of microRNA and epigenetic regulation on silencing and enhancing gene transcription, the study of protein arguably provides more accurate information on homeostasis and perturbation in health and disease. There have been significant advances in the field of proteomics in recent years, with new technologies and platforms available to the research community. In this review, we briefly discuss some of these new technologies and developments in the context of respiratory disease. We also discuss the types of data science approaches to analyses and interpretation of the large volumes of data generated in proteomic studies. We discuss the application of these technologies with regard to respiratory disease and highlight the potential for proteomics in generating major advances in the understanding of respiratory pathophysiology into the future.

Cold and Heat Stress Diversely Alter Both Cauliflower Respiration and Distinct Mitochondrial Proteins Including OXPHOS Components and Matrix Enzymes

Complex proteomic and physiological approaches for studying cold and heat stress responses in plant mitochondria are still limited. Variations in the mitochondrial proteome of cauliflower (Brassica oleracea var. botrytis) curds after cold and heat and after stress recovery were assayed by two-dimensional polyacrylamide gel electrophoresis (2D PAGE) in relation to mRNA abundance and respiratory parameters. Quantitative analysis of the mitochondrial proteome revealed numerous stress-affected protein spots. In cold, major downregulations in the level of photorespiratory enzymes, porine isoforms, oxidative phosphorylation (OXPHOS) and some low-abundant proteins were observed. In contrast, carbohydrate metabolism enzymes, heat-shock proteins, translation, protein import, and OXPHOS components were involved in heat response and recovery. Several transcriptomic and metabolic regulation mechanisms are also suggested. Cauliflower plants appeared less susceptible to heat; closed stomata in heat stress resulted in moderate photosynthetic, but only minor respiratory impairments, however, photosystem II performance was unaffected. Decreased photorespiration corresponded with proteomic alterations in cold. Our results show that cold and heat stress not only operate in diverse modes (exemplified by cold-specific accumulation of some heat shock proteins), but exert some associations at molecular and physiological levels. This implies a more complex model of action of investigated stresses on plant mitochondria.

PRmePRed: A protein arginine methylation prediction tool

Protein methylation is an important Post-Translational Modification (PTMs) of proteins. Arginine methylation carries out and regulates several important biological functions, including gene regulation and signal transduction. Experimental identification of arginine methylation site is a daunting task as it is costly as well as time and labour intensive. Hence reliable prediction tools play an important task in rapid screening and identification of possible methylation sites in proteomes. Our preliminary assessment using the available prediction methods on collected data yielded unimpressive results. This motivated us to perform a comprehensive data analysis and appraisal of features relevant in the context of biological significance, that led to the development of a prediction tool PRmePRed with better performance. The PRmePRed perform reasonably well with an accuracy of 84.10%, 82.38% sensitivity, 83.77% specificity, and Matthew’s correlation coefficient of 66.20% in 10-fold cross-validation. PRmePRed is freely available at http://bioinfo.icgeb.res.in/PRmePRed/

Proteomic approaches to decipher cancer cell secretome

In this review, we give an overview of the actual proteomic approaches used in the study of cancer cells secretome. In particular, we describe the proteomic strategies to decipher cancer cell secretome initially focusing on the different aspects of sample preparation. We examine the issues related to the presence of low abundant proteins, the analysis of secreted proteins in the conditioned media with or without the removal of fetal bovine serum and strategies developed to reduce intracellular protein contamination. As regards the identification and quantification of secreted proteins, we described the different proteomic approaches used, i.e. gel-based, MS-based (label-based and label-free), and the antibody and array-based methods, together with some of the most recent applications in the field of cancer research. Moreover, we describe the bioinformatics tools developed for the in silico validation and characterization of cancer cells secretome. We also discuss the most important available tools for protein annotation and for prediction of classical and non-classical secreted proteins. In summary in this review advances, concerns and challenges in the field of cancer secretome analysis are discussed.

STAT3 Undergoes Acetylation-dependent Mitochondrial Translocation to Regulate Pyruvate Metabolism

Cytoplasmic STAT3, after activation by growth factors, translocates to different subcellular compartments, including nuclei and mitochondria, where it carries out different biological functions. However, the precise mechanism by which STAT3 undergoes mitochondrial translocation and subsequently regulates the tricarboxylic acid (TCA) cycle-electron transport chain (ETC) remains poorly understood. Here, we clarify this process by visualizing STAT3 acetylation in starved cells after serum reintroduction or insulin stimulation. CBP-acetylated STAT3 undergoes mitochondrial translocation in response to serum introduction or insulin stimulation. In mitochondria, STAT3 associates with the pyruvate dehydrogenase complex E1 (PDC-E1) and subsequently accelerates the conversion of pyruvate to acetyl-CoA, elevates the mitochondrial membrane potential, and promotes ATP synthesis. SIRT5 deacetylates STAT3, thereby inhibiting its function in mitochondrial pyruvate metabolism. In the A549 lung cancer cell line, constitutively acetylated STAT3 localizes to mitochondria, where it maintains the mitochondrial membrane potential and ATP synthesis in an active state.

Characterization of in vivo phosphorylation modification of differentially accumulated proteins in cotton fiber-initiation process

Initiation of cotton fiber from ovule epidermal cells determines the ultimate number of fibers per cotton ovule, making it one of the restriction factors of cotton fiber yield. Previous comparative proteomics studies have collectively revealed 162 important differentially accumulated proteins (DAPs) in cotton fiber-initiation process, however, whether and how post-translational modifications, especially phosphorylation modification, regulate the expression and function of the DAPs are still unclear. Here we reported the successful identification of 17 phosphopeptides from 16 phosphoproteins out of the 162 DAPs using the integrated bioinformatics analyses of peptide mass fingerprinting data and targeted MS/MS identification method. In-depth analyses indicated that 15 of the 17 phosphorylation sites were novel phosphorylation sites first identified in plants, whereas 6 of the 16 phosphoproteins were found to be the phosphorylated isoforms of 6 proteins. The phosphorylation-regulated dynamic protein network derived from this study not only expanded our understanding of the cotton fiber-initiation process, but also provided a valuable resource for future functional studies of the phosphoproteins.

Perspectives and Insights into the Competition for Aminoacyl-tRNAs between the Translational Machinery and for tRNA Dependent Non-Ribosomal Peptide Bond Formation

Aminoacyl-tRNA protein transferases catalyze the transfer of amino acids from aminoacyl-tRNAs to polypeptide substrates. Different forms of these enzymes are found in the different kingdoms of life and have been identified to be central to a wide variety of cellular processes. L/F-transferase is the sole member of this class of enzyme found in Escherichia coli and catalyzes the transfer of leucine to the N-termini of proteins which result in the targeted degradation of the modified protein. Recent investigations on the tRNA specificity of L/F-transferase have revealed the unique recognition nucleotides for a preferred Leu-tRNA^Leu isoacceptor substrate. In addition to discussing this tRNA selectivity by L/F-transferase, we present and discuss a hypothesis and its implications regarding the apparent competition for this aminoacyl-tRNA between L/F-transferase and the translational machinery. Our discussion reveals a hypothetical involvement of the bacterial stringent response that occurs upon amino acid limitation as a potential cellular event that may reduce this competition and provide the opportunity for L/F-transferase to readily increase its access to the pool of aminoacylated tRNA substrates.

Flagellin glycosylation in Paenibacillus alvei CCM 2051T

Flagellin glycosylation impacts, in several documented cases, the functionality of bacterial flagella. The basis of flagellin glycosylation has been studied for various Gram-negative bacteria, but less is known about flagellin glycans of Gram-positive bacteria including Paenibacillus alvei, a secondary invader of honeybee colonies diseased with European foulbrood. Paenibacillus alvei CCM 2051(T) swarms vigorously on solidified culture medium, with swarming relying on functional flagella as evidenced by abolished biofilm formation of a non-motile P. alvei mutant defective in the flagellin protein Hag. Here, the glycobiology of the polar P. alvei flagella was investigated. Analysis on purified flagellin demonstrated that the 30-kDa Hag protein (PAV_2c01710) is modified with an O-linked trisaccharide comprised of one hexose and two N-acetyl-hexosamine residues, at three sites of glycosylation. Downstream of the hag gene on the bacterial chromosome, two open reading frames (PAV_2c01630, PAV_2c01640) encoding putative glycosyltransferases were shown to constitute a flagellin glycosylation island. Mutants defective in these genes exhibited altered migration in sodium dodecyl sulfate polyacrylamide gel electrophoresis as well as loss of extracellular flagella production and bacterial motility. This study reveals that flagellin glycosylation in P. alvei is pivotal to flagella formation and bacterial motility in vivo, and simultaneously identifies flagella glycosylation as a second protein O-glycosylation system in this bacterium, in addition to the well-investigated S-layer tyrosine O-glycosylation pathway.

Cell-selective labelling of proteomes in Drosophila melanogaster

The specification and adaptability of cells rely on changes in protein composition. Nonetheless, uncovering proteome dynamics with cell-type-specific resolution remains challenging. Here we introduce a strategy for cell-specific analysis of newly synthesized proteomes by combining targeted expression of a mutated methionyl-tRNA synthetase (MetRS) with bioorthogonal or fluorescent non-canonical amino-acid-tagging techniques (BONCAT or FUNCAT). Substituting leucine by glycine within the MetRS-binding pocket (MetRS^LtoG) enables incorporation of the non-canonical amino acid azidonorleucine (ANL) instead of methionine during translation. Newly synthesized proteins can thus be labelled by coupling the azide group of ANL to alkyne-bearing tags through ‘click chemistry'. To test these methods for applicability in vivo, we expressed MetRS^LtoG cell specifically in Drosophila. FUNCAT and BONCAT reveal ANL incorporation into proteins selectively in cells expressing the mutated enzyme. Cell-type-specific FUNCAT and BONCAT, thus, constitute eligible techniques to study protein synthesis-dependent processes in complex and behaving organisms.

Mutated tRNA synthetases can incorporate non-canonical amino acids into proteins. Erdmann et al. exploit this property to metabolically label newly synthesized proteins in selected cell types in Drosophila, and demonstrate their detection using proteomics (BONCAT) and fluorescence imaging (FUNCAT).

Bioinformatics-Aided Venomics

Venomics is a modern approach that combines transcriptomics and proteomics to explore the toxin content of venoms. This review will give an overview of computational approaches that have been created to classify and consolidate venomics data, as well as algorithms that have helped discovery and analysis of toxin nucleic acid and protein sequences, toxin three-dimensional structures and toxin functions. Bioinformatics is used to tackle specific challenges associated with the identification and annotations of toxins. Recognizing toxin transcript sequences among second generation sequencing data cannot rely only on basic sequence similarity because toxins are highly divergent. Mass spectrometry sequencing of mature toxins is challenging because toxins can display a large number of post-translational modifications. Identifying the mature toxin region in toxin precursor sequences requires the prediction of the cleavage sites of proprotein convertases, most of which are unknown or not well characterized. Tracing the evolutionary relationships between toxins should consider specific mechanisms of rapid evolution as well as interactions between predatory animals and prey. Rapidly determining the activity of toxins is the main bottleneck in venomics discovery, but some recent bioinformatics and molecular modeling approaches give hope that accurate predictions of toxin specificity could be made in the near future.

Flies expand the repertoire of protein structures that bind ice

An antifreeze protein (AFP) with no known homologs has been identified in Lake Ontario midges (Chironomidae). The midge AFP is expressed as a family of isoforms at low levels in adults, which emerge from fresh water in spring before the threat of freezing temperatures has passed. The 9.1-kDa major isoform derived from a preproprotein precursor is glycosylated and has a 10-residue tandem repeating sequence xxCxGxYCxG, with regularly spaced cysteines, glycines, and tyrosines comprising one-half its 79 residues. Modeling and molecular dynamics predict a tightly wound left-handed solenoid fold in which the cysteines form a disulfide core to brace each of the eight 10-residue coils. The solenoid is reinforced by intrachain hydrogen bonds, side-chain salt bridges, and a row of seven stacked tyrosines on the hydrophobic side that forms the putative ice-binding site. A disulfide core is also a feature of the similar-sized beetle AFP that is a β-helix with seven 12-residue coils and a comparable circular dichroism spectrum. The midge and beetle AFPs are not homologous and their ice-binding sites are radically different, with the latter comprising two parallel arrays of outward-pointing threonines. However, their structural similarities is an amazing example of convergent evolution in different orders of insects to cope with change to a colder climate and provide confirmation about the physical features needed for a protein to bind ice.

Overview of software options for processing, analysis and interpretation of mass spectrometric proteomic data

Recently, the interests in proteomics have been intensively increased, and the proteomic methods have been widely applied to many problems in cell biology. If the age of 1990s is considered to be a decade of genomics, we can claim that the following years of the new century is a decade of proteomics. The rapid evolution of proteomics has continued through these years, with a series of innovations in separation techniques and the core technologies of two-dimensional gel electrophoresis and MS. Both technologies are fueled by automation and high throughput computation for profiling of proteins from biological systems. As Patterson ever mentioned, 'data analysis is the Achilles heel of proteomics and our ability to generate data now outstrips our ability to analyze it'. The development of automatic and high throughput technologies for rapid identification of proteins is essential for large-scale proteome projects and automatic protein identification and characterization is essential for high throughput proteomics. This review provides a snap shot of the tools and applications that are available for mass spectrometric high throughput biocomputation. The review starts with a brief introduction of proteomics and MS. Computational tools that can be employed at various stages of analysis are presented, including that for data processing, identification, quantification, and the understanding of the biological functions of individual proteins and their dynamic interactions. The challenges of computation software development and its future trends in MS-based proteomics have also been speculated.

N-glycosylation is required for secretion and enzymatic activity of human hyaluronidase1

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Hyaluronidase1 (HYAL1) is N-glycosylated at Asn⁹⁹, Asn²¹⁶, and Asn³⁵⁰.

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N-glycosylation regulates secretion of HYAL1.

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N-glycosylation is important for enzymatic activity of HYAL1.

Hyaluronidase1 (HYAL1) is a hydrolytic enzyme that degrades hyaluronic acid (HA) and has three predicted N-glycosylation sites at Asn⁹⁹, Asn²¹⁶, and Asn³⁵⁰. In this report, we show the functional significance of N-glycosylation on HYAL1 functions. Using mass spectrometry, we demonstrated that HYAL1 was N-glycosylated at the three asparagine residues. N-glycosylation of HYAL1 is important for secretion of HYAL1, as demonstrated by site-directed mutation. Moreover, a defect of N-glycosylation attenuated the enzymatic activity of HYAL1. Thus, HYAL1 is N-glycosylated at the three asparagine residues, and its secretion and enzymatic activity are regulated by N-glycosylation.

PTM-SD: a database of structurally resolved and annotated posttranslational modifications in proteins

Posttranslational modifications (PTMs) define covalent and chemical modifications of protein residues. They play important roles in modulating various biological functions. Current PTM databases contain important sequence annotations but do not provide informative 3D structural resource about these modifications. Posttranslational modification structural database (PTM-SD) provides access to structurally solved modified residues, which are experimentally annotated as PTMs. It combines different PTM information and annotation gathered from other databases, e.g. Protein DataBank for the protein structures and dbPTM and PTMCuration for fine sequence annotation. PTM-SD gives an accurate detection of PTMs in structural data. PTM-SD can be browsed by PDB id, UniProt accession number, organism and classic PTM annotation. Advanced queries can also be performed, i.e. detailed PTM annotations, amino acid type, secondary structure, SCOP class classification, PDB chain length and number of PTMs by chain. Statistics and analyses can be computed on a selected dataset of PTMs. Each PTM entry is detailed in a dedicated page with information on the protein sequence, local conformation with secondary structure and Protein Blocks. PTM-SD gives valuable information on observed PTMs in protein 3D structure, which is of great interest for studying sequence-structure- function relationships at the light of PTMs, and could provide insights for comparative modeling and PTM predictions protocols. Database URL: PTM-SD can be accessed at http://www.dsimb.inserm.fr/dsimb_tools/PTM-SD/.

Accelerating the scoring module of mass spectrometry-based peptide identification using GPUs

Background

Tandem mass spectrometry-based database searching is currently the main method for protein identification in shotgun proteomics. The explosive growth of protein and peptide databases, which is a result of genome translations, enzymatic digestions, and post-translational modifications (PTMs), is making computational efficiency in database searching a serious challenge. Profile analysis shows that most search engines spend 50%-90% of their total time on the scoring module, and that the spectrum dot product (SDP) based scoring module is the most widely used. As a general purpose and high performance parallel hardware, graphics processing units (GPUs) are promising platforms for speeding up database searches in the protein identification process.

Results

We designed and implemented a parallel SDP-based scoring module on GPUs that exploits the efficient use of GPU registers, constant memory and shared memory. Compared with the CPU-based version, we achieved a 30 to 60 times speedup using a single GPU. We also implemented our algorithm on a GPU cluster and achieved an approximately favorable speedup.

Conclusions

Our GPU-based SDP algorithm can significantly improve the speed of the scoring module in mass spectrometry-based protein identification. The algorithm can be easily implemented in many database search engines such as X!Tandem, SEQUEST, and pFind. A software tool implementing this algorithm is available at http://www.comp.hkbu.edu.hk/~youli/ProteinByGPU.html

Post-translational modification of proteins in toxicological research: focus on lysine acylation

Toxicoproteomics integrates the proteomic knowledge into toxicology by enabling protein quantification in biofluids and tissues, thus taking toxicological research to the next level. Post-translational modification (PTM) alters the three-dimensional (3D) structure of proteins by covalently binding small molecules to them and therefore represents a major protein function diversification mechanism. Because of the crucial roles PTM plays in biological systems, the identification of novel PTMs and study of the role of PTMs are gaining much attention in proteomics research. Of the 300 known PTMs, protein acylation, including lysine formylation, acetylation, propionylation, butyrylation, malonylation, succinylation, and crotonylation, regulates the crucial functions of many eukaryotic proteins involved in cellular metabolism, cell cycle, aging, growth, angiogenesis, and cancer. Here, I reviewed recent studies regarding novel types of lysine acylation, their biological functions, and their applicationsin toxicoproteomics research.

Mass spectrometric identification of in vivo phosphorylation sites of differentially expressed proteins in elongating cotton fiber cells

Two-dimensional gel electrophoresis (2-DE)-based proteomics approach was applied to extensively explore the molecular basis of plant development and environmental adaptation. These proteomics analyses revealed thousands of differentially expressed proteins (DEPs) closely related to different biological processes. However, little attention has been paid to how peptide mass fingerprinting (PMF) data generated by the approach can be directly utilized for the determination of protein phosphorylation. Here, we used the software tool FindMod to predict the peptides that might carry the phosphorylation modification by examining their PMF data for mass differences between the empirical and theoretical peptides and then identified phosphorylation sites using MALDI TOF/TOF according to predicted peptide data from these DEP spots in the 2-D gels. As a result, a total of 48 phosphorylation sites of 40 DEPs were successfully identified among 235 known DEPs previously revealed in the 2-D gels of elongating cotton fiber cells. The 40 phosphorylated DEPs, including important enzymes such as enolase, transketolase and UDP-L-rhamnose synthase, are presumed to participate in the functional regulation of numerous metabolic pathways, suggesting the reverse phosphorylation of these proteins might play important roles in elongating cotton fibers. The results also indicated that some different isoforms of the identical DEP revealed in our 2-DE-based proteomics analysis could be annotated by phosphorylation events. Taken together, as the first report of large-scale identification of phosphorylation sites in elongating cotton fiber cells, our study provides not only an excellent example of directly identifying phosphorylation sites from known DEPs on 2-D gels but also provides a valuable resource for future functional studies of phosphorylated proteins in this field.

Mass spectrometry-based proteomics for the analysis of chromatin structure and dynamics

Chromatin is a highly structured nucleoprotein complex made of histone proteins and DNA that controls nearly all DNA-dependent processes. Chromatin plasticity is regulated by different associated proteins, post-translational modifications on histones (hPTMs) and DNA methylation, which act in a concerted manner to enforce a specific "chromatin landscape", with a regulatory effect on gene expression. Mass Spectrometry (MS) has emerged as a powerful analytical strategy to detect histone PTMs, revealing interplays between neighbouring PTMs and enabling screens for their readers in a comprehensive and quantitative fashion. Here we provide an overview of the recent achievements of state-of-the-art mass spectrometry-based proteomics for the detailed qualitative and quantitative characterization of histone post-translational modifications, histone variants, and global interactomes at specific chromatin regions. This synopsis emphasizes how the advances in high resolution MS, from "Bottom Up" to "Top Down" analysis, together with the uptake of quantitative proteomics methods by chromatin biologists, have made MS a well-established method in the epigenetics field, enabling the acquisition of original information, highly complementary to that offered by more conventional, antibody-based, assays.

High yield production of myristoylated Arf6 small GTPase by recombinant N-myristoyl transferase

Small GTP-binding proteins of the Arf family (Arf GTPases) interact with multiple cellular partners and with membranes to regulate intracellular traffic and organelle structure. Understanding the underlying molecular mechanisms requires in vitro biochemical assays to test for regulations and functions. Such assays should use proteins in their cellular form, which carry a myristoyl lipid attached in N-terminus. N-myristoylation of recombinant Arf GTPases can be achieved by co-expression in E. coli with a eukaryotic N-myristoyl transferase. However, purifying myristoylated Arf GTPases is difficult and has a poor overall yield. Here we show that human Arf6 can be N-myristoylated in vitro by recombinant N-myristoyl transferases from different eukaryotic species. The catalytic efficiency depended strongly on the guanine nucleotide state and was highest for Arf6-GTP. Large-scale production of highly pure N-myristoylated Arf6 could be achieved, which was fully functional for liposome-binding and EFA6-stimulated nucleotide exchange assays. This establishes in vitro myristoylation as a novel and simple method that could be used to produce other myristoylated Arf and Arf-like GTPases for biochemical assays.

Enhanced methylarginine characterization by post-translational modification-specific targeted data acquisition and electron-transfer dissociation mass spectrometry

When localizing protein post-translational modifications (PTMs) using liquid-chromatography (LC)-tandem mass spectrometry (MS/MS), existing implementations are limited by inefficient selection of PTM-carrying peptides for MS/MS, particularly when PTM site occupancy is sub-stoichiometric. The present contribution describes a method by which peptides carrying specific PTMs of interest-in this study, methylarginines-may be selectively targeted for MS/MS: peptide features are extracted from high mass accuracy single-stage MS data, searched against theoretical PTM-carrying peptide masses, and matching features are subjected to targeted data acquisition LC-MS/MS. Using trypsin digested Saccharomyces cerevisiae Npl3, in which evidence is presented for 18 methylarginine sites-17 of which fall within a glycine-arginine-rich (GAR) domain spanning <120 amino acids-it is shown that this approach outperforms conventional data dependent acquisition (DDA): when applied to a complex protein mixture featuring in vivo methylated Npl3, 95% more (P=0.030) methylarginine-carrying peptides are selected for MS/MS than DDA, leading to an 86% increase (P=0.044) in the number of methylated peptides producing Mascot ion scores ≥20 following electron-transfer dissociation (ETD). Notably, significantly more low abundance arginine methylated peptides (maximum ion intensities <6×10(4) cps) are selected for MS/MS using this approach relative to DDA (50% more in a digest of purified in vitro methylated Npl3). It is also demonstrated that relative to collision-induced dissociation (CID), ETD facilitates a 586% increase (P=0.016) in average Mascot ion scores of methylarginine-carrying peptides. The present PTM-specific targeted data acquisition approach, though described using methylarginine, is applicable to any ionizable PTM of known mass.

Delivering value from sperm proteomics for fertility

Fertilization of an egg by a spermatozoon sets the stage for mammalian development. Viable sperm are a prerequisite for successful fertilization and beyond. Spermatozoa have a unique cell structure where haploid genomic DNA is located in a tiny cytoplasmic space in the head, mitochondria in the midpiece and then the tail, all enclosed by several layers of membrane. Proteins in sperm play vital roles in motility, capacitation, fertilization, egg activation and embryo development. Molecular defects in these proteins are associated with low fertility or in some cases, infertility. This review will first summarize genesis, molecular anatomy and physiology of spermatozoa, fertilization, embryogenesis and then those proteins playing important roles in various aspects of sperm physiology.