Assigning Significance to Peptides Identified by Tandem Mass Spectrometry Using Decoy Databases

Effects of vegetative propagation on protein content and bioactivity of the red seaweed Palmaria palmata

Production of the red seaweed Palmaria palmata is currently hindered by a lack of standardised cultivation methods leading to uncertainties in yield and product quality. This study assessed vegetative propagation of meristematic fragments and the protein content and bioactivity potential of resulting plants. Growth was strong and sustained, averaging 5% day-1. Total protein contents initially decreased but recovered as the fragments grew larger and thicker. Samples displayed the highest antioxidant activity early in the experiment, suggesting that wounds may increase the secretion of antioxidant compounds. In silico analysis identified 762 potentially bioactive motifs, including 70 matching in vitro results. The newly discovered peptide SLLYSDITRPGGNMYTTR (SR18), linked to the pigment allophycocyanin, had very strong antioxidant properties and may drive the recorded in vitro activity. Vegetative propagation appears as a strong potential cultivation tool, and the utilised approach can be applied to assess the cultivation and nutritional potential of other seaweed species.

An algorithm for decoy-free false discovery rate estimation in XL-MS/MS proteomics

MOTIVATION

Cross-linking tandem mass spectrometry (XL-MS/MS) is an established analytical platform used to determine distance constraints between residues within a protein or from physically interacting proteins, thus improving our understanding of protein structure and function. To aid biological discovery with XL-MS/MS, it is essential that pairs of chemically linked peptides be accurately identified, a process that requires: (i) database search, that creates a ranked list of candidate peptide pairs for each experimental spectrum and (ii) false discovery rate (FDR) estimation, that determines the probability of a false match in a group of top-ranked peptide pairs with scores above a given threshold. Currently, the only available FDR estimation mechanism in XL-MS/MS is the target-decoy approach (TDA). However, despite its simplicity, TDA has both theoretical and practical limitations that impact the estimation accuracy and increase run time over potential decoy-free approaches (DFAs).

RESULTS

We introduce a novel decoy-free framework for FDR estimation in XL-MS/MS. Our approach relies on multi-sample mixtures of skew normal distributions, where the latent components correspond to the scores of correct peptide pairs (both peptides identified correctly), partially incorrect peptide pairs (one peptide identified correctly, the other incorrectly), and incorrect peptide pairs (both peptides identified incorrectly). To learn these components, we exploit the score distributions of first- and second-ranked peptide-spectrum matches for each experimental spectrum and subsequently estimate FDR using a novel expectation-maximization algorithm with constraints. We evaluate the method on ten datasets and provide evidence that the proposed DFA is theoretically sound and a viable alternative to TDA owing to its good performance in terms of accuracy, variance of estimation, and run time.

AVAILABILITY AND IMPLEMENTATION

https://github.com/shawn-peng/xlms.

Exact Integral Formulas for False Discovery Rate and the Variance of False Discovery Proportion

Multiple hypothesis testing is an integral component of data analysis for large-scale technologies such as proteomics, transcriptomics, or metabolomics, for which the false discovery rate (FDR) and positive FDR (pFDR) have been accepted as error estimation and control measures. The pFDR is the expectation of false discovery proportion (FDP), which refers to the ratio of the number of null hypotheses to that of all rejected hypotheses. In practice, the expectation of ratio is approximated by the ratio of expectation; however, the conditions for transforming the former into the latter have not been investigated. This work derives exact integral expressions for the expectation (pFDR) and variance of FDP. The widely used approximation (ratio of expectations) is shown to be a particular case (in the limit of a large sample size) of the integral formula for pFDR. A recurrence formula is provided to compute the pFDR for a predefined number of null hypotheses. The variance of FDP was approximated for a practical application in peptide identification using forward and reversed protein sequences. The simulations demonstrate that the integral expression exhibits better accuracy than the approximate formula in the case of a small number of hypotheses. For large sample sizes, the pFDRs obtained by the integral expression and approximation do not differ substantially. Applications to proteomics data sets are included.

The MBO2/FAP58 heterodimer stabilizes assembly of inner arm dynein b and reveals axoneme asymmetries involved in ciliary waveform

Cilia generate three-dimensional waveforms required for cell motility and transport of fluid, mucus, and particles over the cell surface. This movement is driven by multiple dynein motors attached to nine outer doublet microtubules that form the axoneme. The outer and inner arm dyneins are organized into 96-nm repeats tandemly arrayed along the length of the doublets. Motility is regulated in part by projections from the two central pair microtubules that contact radial spokes located near the base of the inner dynein arms in each repeat. Although much is known about the structures and protein complexes within the axoneme, many questions remain about the regulatory mechanisms that allow the cilia to modify their waveforms in response to internal or external stimuli. Here, we used Chlamydomonas mbo (move backwards only) mutants with altered waveforms to identify at least two conserved proteins, MBO2/CCDC146 and FAP58/CCDC147, that form part of a L-shaped structure that varies between doublet microtubules. Comparative proteomics identified additional missing proteins that are altered in other motility mutants, revealing overlapping protein defects. Cryo-electron tomography and epitope tagging revealed that the L-shaped, MBO2/FAP58 structure interconnects inner dynein arms with multiple regulatory complexes, consistent with its function in modifying the ciliary waveform.

Label-free quantitative proteomics in serum reveals candidate biomarkers associated with low bone mineral density in Mexican postmenopausal women

Postmenopausal osteoporosis is a public health problem leading to an increased risk of fractures, negatively impacting women's health. The absence of sensitive and specific biomarkers for early detection of osteoporosis represents a substantial challenge for improving patient management. Herein, we aimed to identify potential candidate proteins associated with low bone mineral density (BMD) in postmenopausal women from the Mexican population. Serum samples from postmenopausal women (40 with normal BMD, 40 with osteopenia (OS), and 20 with osteoporosis (OP)) were analyzed by label-free LC-MS/MS quantitative proteomics. Proteome profiling revealed significant differences between the OS and OP groups compared to individuals with normal BMD. A quantitative comparison of proteins between groups indicated 454 differentially expressed proteins (DEPs). Compared to normal BMD, 14 and 214 DEPs were found in OS and OP groups, respectively, while 226 DEPs were identified between OS and OP groups. The protein-protein interaction and enrichment analysis of DEPs were closely linked to the bone mineral content, skeletal morphology, and immune response activation. Based on their role in bone metabolism, a panel of 12 candidate biomarkers was selected, of which 1 DEP (RYR1) was found upregulated in the OS and OP groups, 8 DEPs (APOA1, SHBG, FETB, MASP1, PTK2B, KNG1, GSN, and B2M) were upregulated in OP and 3 DEPs (APOA2, RYR3, and HBD) were downregulated in OS or OP. The proteomic analysis described here may help discover new and potentially non-invasive biomarkers for the early diagnosis of osteoporosis in postmenopausal women.

MS2Rescore 3.0 Is a Modular, Flexible, and User-Friendly Platform to Boost Peptide Identifications, as Showcased with MS Amanda 3.0

Rescoring of peptide-spectrum matches (PSMs) has emerged as a standard procedure for the analysis of tandem mass spectrometry data. This emphasizes the need for software maintenance and continuous improvement for such algorithms. We introduce MS2Rescore 3.0, a versatile, modular, and user-friendly platform designed to increase peptide identifications. Researchers can install MS2Rescore across various platforms with minimal effort and benefit from a graphical user interface, a modular Python API, and extensive documentation. To showcase this new version, we connected MS2Rescore 3.0 with MS Amanda 3.0, a new release of the well-established search engine, addressing previous limitations on automatic rescoring. Among new features, MS Amanda now contains additional output columns that can be used for rescoring. The full potential of rescoring is best revealed when applied on challenging data sets. We therefore evaluated the performance of these two tools on publicly available single-cell data sets, where the number of PSMs was substantially increased, thereby demonstrating that MS2Rescore offers a powerful solution to boost peptide identifications. MS2Rescore's modular design and user-friendly interface make data-driven rescoring easily accessible, even for inexperienced users. We therefore expect the MS2Rescore to be a valuable tool for the wider proteomics community. MS2Rescore is available at https://github.com/compomics/ms2rescore.

Ion entropy and accurate entropy-based FDR estimation in metabolomics

Accurate metabolite annotation and false discovery rate (FDR) control remain challenging in large-scale metabolomics. Recent progress leveraging proteomics experiences and interdisciplinary inspirations has provided valuable insights. While target-decoy strategies have been introduced, generating reliable decoy libraries is difficult due to metabolite complexity. Moreover, continuous bioinformatics innovation is imperative to improve the utilization of expanding spectral resources while reducing false annotations. Here, we introduce the concept of ion entropy for metabolomics and propose two entropy-based decoy generation approaches. Assessment of public databases validates ion entropy as an effective metric to quantify ion information in massive metabolomics datasets. Our entropy-based decoy strategies outperform current representative methods in metabolomics and achieve superior FDR estimation accuracy. Analysis of 46 public datasets provides instructive recommendations for practical application.

Cylicins are a structural component of the sperm calyx being indispensable for male fertility in mice and human

Cylicins are testis-specific proteins, which are exclusively expressed during spermiogenesis. In mice and humans, two Cylicins, the gonosomal X-linked Cylicin 1 (Cylc1/CYLC1) and the autosomal Cylicin 2 (Cylc2/CYLC2) genes, have been identified. Cylicins are cytoskeletal proteins with an overall positive charge due to lysine-rich repeats. While Cylicins have been localized in the acrosomal region of round spermatids, they resemble a major component of the calyx within the perinuclear theca at the posterior part of mature sperm nuclei. However, the role of Cylicins during spermiogenesis has not yet been investigated. Here, we applied CRISPR/Cas9-mediated gene editing in zygotes to establish Cylc1- and Cylc2-deficient mouse lines as a model to study the function of these proteins. Cylc1 deficiency resulted in male subfertility, whereas Cylc2-/-, Cylc1-/yCylc2+/-, and Cylc1-/yCylc2-/- males were infertile. Phenotypical characterization revealed that loss of Cylicins prevents proper calyx assembly during spermiogenesis. This results in decreased epididymal sperm counts, impaired shedding of excess cytoplasm, and severe structural malformations, ultimately resulting in impaired sperm motility. Furthermore, exome sequencing identified an infertile man with a hemizygous variant in CYLC1 and a heterozygous variant in CYLC2, displaying morphological abnormalities of the sperm including the absence of the acrosome. Thus, our study highlights the relevance and importance of Cylicins for spermiogenic remodeling and male fertility in human and mouse, and provides the basis for further studies on unraveling the complex molecular interactions between perinuclear theca proteins required during spermiogenesis.

Analysis of CDPK1 targets identifies a trafficking adaptor complex that regulates microneme exocytosis in Toxoplasma

Apicomplexan parasites use Ca2+-regulated exocytosis to secrete essential virulence factors from specialized organelles called micronemes. Ca2+-dependent protein kinases (CDPKs) are required for microneme exocytosis; however, the molecular events that regulate trafficking and fusion of micronemes with the plasma membrane remain unresolved. Here, we combine sub-minute resolution phosphoproteomics and bio-orthogonal labeling of kinase substrates in Toxoplasma gondii to identify 163 proteins phosphorylated in a CDPK1-dependent manner. In addition to known regulators of secretion, we identify uncharacterized targets with predicted functions across signaling, gene expression, trafficking, metabolism, and ion homeostasis. One of the CDPK1 targets is a putative HOOK activating adaptor. In other eukaryotes, HOOK homologs form the FHF complex with FTS and FHIP to activate dynein-mediated trafficking of endosomes along microtubules. We show the FHF complex is partially conserved in T. gondii, consisting of HOOK, an FTS homolog, and two parasite-specific proteins (TGGT1_306920 and TGGT1_316650). CDPK1 kinase activity and HOOK are required for the rapid apical trafficking of micronemes as parasites initiate motility. Moreover, parasites lacking HOOK or FTS display impaired microneme protein secretion, leading to a block in the invasion of host cells. Taken together, our work provides a comprehensive catalog of CDPK1 targets and reveals how vesicular trafficking has been tuned to support a parasitic lifestyle.

Use of AgomiR and AntagomiR technologies to alter satellite cell proliferation in vitro, miRNA expression, and muscle fiber hypertrophy in intrauterine growth-restricted lambs

Introduction: microRNAs (miRNAs) are small non-coding RNAs that work at the posttranscriptional level to repress gene expression. Several miRNAs are preferentially expressed in skeletal muscle and participate in myogenesis. This research was conducted to alter endogenous miRNA expression in skeletal muscle to promote muscle hypertrophy. Methods: Two experiments were conducted using mimic/agomiR or antagomir technologies to alter miRNA expression and examine changes in myoblast proliferation in vitro (experiment 1) and muscle hypertrophy in vivo (experiment 2). In vitro experiments found that antagomiR-22-3p and mimic-127 increased myoblast proliferation compared to other miRNA treatments or controls. These miRNA treatments, antagomiR-22-3p (ANT22) and agomiR-127 (AGO127), were then used for intramuscular injections in longissimus muscle. Results and discussion: The use of antagomiR or mimic/agomiR treatments down-regulated or up-regulated, respectively, miRNA expression for that miRNA of interest. Expression of predicted target KIF3B mRNA for miR-127 was up-regulated and ACVR2a mRNA was up-regulated for miR-22-3p. ANT22 injection also up-regulated the major regulator of protein synthesis (mTOR). Proteomic analyses identified 11 proteins for AGO127 and 9 proteins for ANT22 that were differentially expressed. Muscle fiber type and cross-sectional area were altered for ANT22 treatments to transition fibers to a more oxidative state. The use of agomiR and antagomir technologies allows us to alter miRNA expression in vitro and in vivo to enhance myoblast proliferation and alter muscle fiber hypertrophy in IUGR lambs during early postnatal growth.

Characterization of a recombinant factor IX molecule fused to coagulation factor XIII-B subunit

INTRODUCTION AND AIM

Severe haemophilia B (HB) is characterized by spontaneous bleeding episodes, mostly into joints. Recurrent bleeds lead to progressive joint destruction called haemophilic arthropathy. The current concept of prophylaxis aims at maintaining the FIX level >3-5 IU/dL, which is effective at reducing the incidence of haemophilic arthropathy. Extended half-life FIX molecules make it easier to achieve these target trough levels compared to standard FIX concentrates. We previously reported that the fusion of a recombinant FIX (rFIX) to factor XIII-B (FXIIIB) subunit prolonged the half-life of the rFIX-LXa-FXIIIB fusion molecule in mice and rats 3.9- and 2.2-fold, respectively, compared with rFIX-WT. However, the mechanism behind the extended half-life was not known.

MATERIALS AND METHODS

Mass spectrometry and ITC were used to study interactions of rFIX-LXa-FXIIIB with albumin. Pharmacokinetic analyses in fibrinogen-KO and FcRn-KO mice were performed to evaluate the effect of albumin and fibrinogen on in-vivo half-life of rFIX-LXa-FXIIIB. Finally saphenous vein bleeding model was used to assess in-vivo haemostatic activity of rFIX-LXa-FXIIIB.

RESULTS AND CONCLUSION

We report here the key interactions that rFIX-LXa-FXIIIB may have in plasma are with fibrinogen and albumin which may mediate its prolonged half-life. In addition, using the saphenous vein bleeding model, we demonstrate that rFIX-FXIIIB elicits functional clot formation that is indistinguishable from that of rFIX-WT.

Cell-type specific defects in PTEN-mutant cortical organoids converge on abnormal circuit activity

De novo heterozygous loss-of-function mutations in phosphatase and tensin homolog (PTEN) are strongly associated with autism spectrum disorders; however, it is unclear how heterozygous mutations in this gene affect different cell types during human brain development and how these effects vary across individuals. Here, we used human cortical organoids from different donors to identify cell-type specific developmental events that are affected by heterozygous mutations in PTEN. We profiled individual organoids by single-cell RNA-seq, proteomics and spatial transcriptomics and revealed abnormalities in developmental timing in human outer radial glia progenitors and deep-layer cortical projection neurons, which varied with the donor genetic background. Calcium imaging in intact organoids showed that both accelerated and delayed neuronal development phenotypes resulted in similar abnormal activity of local circuits, irrespective of genetic background. The work reveals donor-dependent, cell-type specific developmental phenotypes of PTEN heterozygosity that later converge on disrupted neuronal activity.

The Research Progress of Bioactive Peptides Derived from Traditional Natural Products in China

Traditional natural products in China have a long history and a vast pharmacological repertoire that has garnered significant attention due to their safety and efficacy in disease prevention and treatment. Among the bioactive components of traditional natural products in China, bioactive peptides (BPs) are specific protein fragments that have beneficial effects on human health. Despite many of the traditional natural products in China ingredients being rich in protein, BPs have not received sufficient attention as a critical factor influencing overall therapeutic efficacy. Therefore, the purpose of this review is to provide a comprehensive summary of the current methodologies for the preparation, isolation, and identification of BPs from traditional natural products in China and to classify the functions of discovered BPs. Insights from this review are expected to facilitate the development of targeted drugs and functional foods derived from traditional natural products in China in the future.

Quantitative proteomic analysis of super soft kernel texture in soft white spring wheat

Super soft kernel texture is associated with superior milling and baking performance in soft wheat. To understand the mechanism underlying super soft kernel texture, we studied proteomic changes between a normal soft and a super soft during kernel development. The cultivar 'Alpowa', a soft white spring wheat, was crossed to a closely related super soft spring wheat line 'BC2SS163' to produce F6 recombinant inbred lines (RILs). Four normal soft RILs and four super soft RILs along with the parents were selected for proteomic analysis. Alpowa and the normal soft RILs showed hardness indices of 20 to 30, whereas BC2SS163 and the super soft RILs showed hardness indices of -2 to -6. Kernels were collected from normal soft and super soft genotypes at 7 days post anthesis (dpa), 14 dpa, 28 dpa, and maturity and were subject to quantitative proteomic analysis. Throughout kernel development, 175 differentially abundant proteins (DAPs) were identified. Most DAPs were observed at 7 dpa, 14 dpa, and 28 dpa. Of the 175 DAPs, 32 had higher abundance in normal soft wheat, whereas 143 DAPs had higher abundance in super soft wheat. A total of 18 DAPs were associated with carbohydrate metabolism and five DAPs were associated with lipids. The gene TraesCS4B02G091100.1 on chromosome arm 4BS, which encodes for sucrose-phosphate synthase, was identified as a candidate gene for super soft kernel texture in BC2SS163. This study enhanced our understanding of the mechanism underlying super soft kernel texture in soft white spring wheat.

Analysis of CDPK1 targets identifies a trafficking adaptor complex that regulates microneme exocytosis in Toxoplasma

Apicomplexan parasites use Ca2+-regulated exocytosis to secrete essential virulence factors from specialized organelles called micronemes. Ca2+-dependent protein kinases (CDPKs) are required for microneme exocytosis; however, the molecular events that regulate trafficking and fusion of micronemes with the plasma membrane remain unresolved. Here, we combine sub-minute resolution phosphoproteomics and bio-orthogonal labeling of kinase substrates in Toxoplasma gondii to identify 163 proteins phosphorylated in a CDPK1-dependent manner. In addition to known regulators of secretion, we identify uncharacterized targets with predicted functions across signaling, gene expression, trafficking, metabolism, and ion homeostasis. One of the CDPK1 targets is a putative HOOK activating adaptor. In other eukaryotes, HOOK homologs form the FHF complex with FTS and FHIP to activate dynein-mediated trafficking of endosomes along microtubules. We show the FHF complex is partially conserved in T. gondii, consisting of HOOK, an FTS homolog, and two parasite-specific proteins (TGGT1_306920 and TGGT1_316650). CDPK1 kinase activity and HOOK are required for the rapid apical trafficking of micronemes as parasites initiate motility. Moreover, parasites lacking HOOK or FTS display impaired microneme protein secretion, leading to a block in the invasion of host cells. Taken together, our work provides a comprehensive catalog of CDPK1 targets and reveals how vesicular trafficking has been tuned to support a parasitic lifestyle.

TOR complex 1 negatively regulates NDR kinase Cbk1 to control cell separation in budding yeast

The target of rapamycin (TOR) signalling pathway plays a key role in the coordination between cellular growth and the cell cycle machinery in eukaryotes. The underlying molecular mechanisms by which TOR might regulate events after anaphase remain unknown. We show for the first time that one of the 2 TOR complexes in budding yeast, TORC1, blocks the separation of cells following cytokinesis by phosphorylation of a member of the NDR (nuclear Dbf2-related) protein-kinase family, the protein Cbk1. We observe that TORC1 alters the phosphorylation pattern of Cbk1 and we identify a residue within Cbk1 activation loop, T574, for which a phosphomimetic substitution makes Cbk1 catalytically inactive and, indeed, reproduces TORC1 control over cell separation. In addition, we identify the exocyst component Sec3 as a key substrate of Cbk1, since Sec3 activates the SNARE complex to promote membrane fusion. TORC1 activity ultimately compromises the interaction between Sec3 and a t-SNARE component. Our data indicate that TORC1 negatively regulates cell separation in budding yeast by participating in Cbk1 phosphorylation, which in turn controls the fusion of secretory vesicles transporting hydrolase at the site of division.

MSBooster: improving peptide identification rates using deep learning-based features

Peptide identification in liquid chromatography-tandem mass spectrometry (LC-MS/MS) experiments relies on computational algorithms for matching acquired MS/MS spectra against sequences of candidate peptides using database search tools, such as MSFragger. Here, we present a new tool, MSBooster, for rescoring peptide-to-spectrum matches using additional features incorporating deep learning-based predictions of peptide properties, such as LC retention time, ion mobility, and MS/MS spectra. We demonstrate the utility of MSBooster, in tandem with MSFragger and Percolator, in several different workflows, including nonspecific searches (immunopeptidomics), direct identification of peptides from data independent acquisition data, single-cell proteomics, and data generated on an ion mobility separation-enabled timsTOF MS platform. MSBooster is fast, robust, and fully integrated into the widely used FragPipe computational platform.

Transplanting FVIII/ET3-secreting cells in fetal sheep increases FVIII levels long-term without inducing immunity or toxicity

Hemophilia A is the most common X-linked bleeding disorder affecting more than half-a-million individuals worldwide. Persons with severe hemophilia A have coagulation FVIII levels <1% and experience spontaneous debilitating and life-threatening bleeds. Advances in hemophilia A therapeutics have significantly improved health outcomes, but development of FVIII inhibitory antibodies and breakthrough bleeds during therapy significantly increase patient morbidity and mortality. Here we use sheep fetuses at the human equivalent of 16-18 gestational weeks, and we show that prenatal transplantation of human placental cells (107-108/kg) bioengineered to produce an optimized FVIII protein, results in considerable elevation in plasma FVIII levels that persists for >3 years post-treatment. Cells engraft in major organs, and none of the recipients mount immune responses to either the cells or the FVIII they produce. Thus, these studies attest to the feasibility, immunologic advantage, and safety of treating hemophilia A prior to birth.

Nuclear lamin A/C phosphorylation by loss of Androgen Receptor is a global determinant of cancer-associated fibroblast activation

Alterations of nuclear structure and function, and associated impact on gene transcription, are a hallmark of cancer cells. Little is known of these alterations in Cancer-Associated Fibroblasts (CAFs), a key component of the tumor stroma. Here we show that loss of androgen receptor (AR), which triggers early steps of CAF activation in human dermal fibroblasts (HDFs), leads to nuclear membrane alterations and increased micronuclei formation, which are unlinked from induction of cellular senescence. Similar alterations occur in fully established CAFs, which are overcome by restored AR function. AR associates with nuclear lamin A/C and loss of AR results in a substantially increased lamin A/C nucleoplasmic redistribution. Mechanistically, AR functions as a bridge between lamin A/C with the protein phosphatase PPP1. In parallel with a decreased lamin-PPP1 association, AR loss results in a marked increase of lamin A/C phosphorylation at Ser 301, which is also a feature of CAFs. Phosphorylated lamin A/C at Ser 301 binds to the transcription promoter regulatory region of several CAF effector genes, which are upregulated due to the loss of AR. More directly, expression of a lamin A/C Ser301 phosphomimetic mutant alone is sufficient to convert normal fibroblasts into tumor-promoting CAFs of the myofibroblast subtype, without an impact on senescence. These findings highlight the pivotal role of the AR-lamin A/C-PPP1 axis and lamin A/C phosphorylation at Ser 301 in driving CAF activation.

An Initial Proteomic Analysis of Biogas-Related Metabolism of Euryarchaeota Consortia in Sediments from the Santiago River, México

In this paper, sediments from the Santiago River were characterized to look for an alternative source of inoculum for biogas production. A proteomic analysis of methane-processing archaea present in these sediments was carried out. The Euryarchaeota superkingdom of archaea is responsible for methane production and methane assimilation in the environment. The Santiago River is a major river in México with great pollution and exceeded recovery capacity. Its sediments could contain nutrients and the anaerobic conditions for optimal growth of Euryarchaeota consortia. Batch bioreactor experiments were performed, and a proteomic analysis was conducted with current database information. The maximum biogas production was 266 NmL·L^-1·g VS^-1, with 33.34% of methane, and for proteomics, 3206 proteins were detected from 303 species of 69 genera. Most of them are metabolically versatile members of the genera Methanosarcina and Methanosarcinales, both with 934 and 260 proteins, respectively. These results showed a diverse euryarcheotic species with high potential to methane production. Although related proteins were found and could be feeding this metabolism through the methanol and acetyl-CoA pathways, the quality obtained from the biogas suggests that this metabolism is not the main one in carbon use, possibly the sum of several conditions including growth conditions and the pollution present in these sediments.

Generalized precursor prediction boosts identification rates and accuracy in mass spectrometry based proteomics

Data independent acquisition mass spectrometry (DIA-MS) has recently emerged as an important method for the identification of blood-based biomarkers. However, the large search space required to identify novel biomarkers from the plasma proteome can introduce a high rate of false positives that compromise the accuracy of false discovery rates (FDR) using existing validation methods. We developed a generalized precursor scoring (GPS) method trained on 2.75 million precursors that can confidently control FDR while increasing the number of identified proteins in DIA-MS independent of the search space. We demonstrate how GPS can generalize to new data, increase protein identification rates, and increase the overall quantitative accuracy. Finally, we apply GPS to the identification of blood-based biomarkers and identify a panel of proteins that are highly accurate in discriminating between subphenotypes of septic acute kidney injury from undepleted plasma to showcase the utility of GPS in discovery DIA-MS proteomics.

Lipid Peroxidation Products Influence Calpain-1 Functionality In Vitro by Covalent Binding

The objective of the current study was to evaluate the effects of lipid peroxidation products, malondialdehyde (MDA), hexenal, and 4-hydroxynonenal (HNE), on calpain-1 function, and liquid chromatography and tandem mass spectrometry (LC-MS/MS) identification of adducts on calpain-1. Calpain-1 activity slightly increased after incubation with 100 μM MDA but not with 500 and 1000 μM MDA. However, calpain-1 activity was lowered by hexenal and HNE at 100, 500, and 1000 μM. No difference in calpain-1 autolysis was observed between the control and 1000 μM MDA. However, 1000 μM hexenal and HNE treatments slowed the calpain-1 autolysis. Adducts of MDA were detected on glutamine, arginine, lysine, histidine, and asparagine residues via Schiff base formation, while HNE adducts were detected on histidine, lysine, glutamine, and asparagine residues via Michael addition. These results are the first to demonstrate that lipid peroxidation products can impact calpain-1 activity in a concentration-dependent manner and may impact the development of meat tenderness postmortem.

Amino acid sequence assignment from single molecule peptide sequencing data using a two-stage classifier

We present a machine learning-based interpretive framework (whatprot) for analyzing single molecule protein sequencing data produced by fluorosequencing, a recently developed proteomics technology that determines sparse amino acid sequences for many individual peptide molecules in a highly parallelized fashion. Whatprot uses Hidden Markov Models (HMMs) to represent the states of each peptide undergoing the various chemical processes during fluorosequencing, and applies these in a Bayesian classifier, in combination with pre-filtering by a k-Nearest Neighbors (kNN) classifier trained on large volumes of simulated fluorosequencing data. We have found that by combining the HMM based Bayesian classifier with the kNN pre-filter, we are able to retain the benefits of both, achieving both tractable runtimes and acceptable precision and recall for identifying peptides and their parent proteins from complex mixtures, outperforming the capabilities of either classifier on its own. Whatprot's hybrid kNN-HMM approach enables the efficient interpretation of fluorosequencing data using a full proteome reference database and should now also enable improved sequencing error rate estimates.

Spatial probabilistic mapping of metabolite ensembles in mass spectrometry imaging

Mass spectrometry imaging vows to enable simultaneous spatially resolved investigation of hundreds of metabolites in tissues, but it primarily relies on traditional ion images for non-data-driven metabolite visualization and analysis. The rendering and interpretation of ion images neither considers nonlinearities in the resolving power of mass spectrometers nor does it yet evaluate the statistical significance of differential spatial metabolite abundance. Here, we outline the computational framework moleculaR ( https://github.com/CeMOS-Mannheim/moleculaR ) that is expected to improve signal reliability by data-dependent Gaussian-weighting of ion intensities and that introduces probabilistic molecular mapping of statistically significant nonrandom patterns of relative spatial abundance of metabolites-of-interest in tissue. moleculaR also enables cross-tissue statistical comparisons and collective molecular projections of entire biomolecular ensembles followed by their spatial statistical significance evaluation on a single tissue plane. It thereby fosters the spatially resolved investigation of ion milieus, lipid remodeling pathways, or complex scores like the adenylate energy charge within the same image.

Modeling Lower-Order Statistics to Enable Decoy-Free FDR Estimation in Proteomics

One of the chief objectives in mass spectrometry-based peptide identification in proteomics is the statistical validation of top-scoring peptide-spectrum matches (PSMs) in the form of false discovery rate (FDR) estimation. Existing methods construct a null model that captures the characteristics of incorrect target PSMs to estimate the FDR, most often with the help of decoys. Decoy-based methods, however, increase the computational cost and rely on the difficult-to-verify assumption that decoy PSMs constitute a sufficient and representative sample of the population of possible incorrect target PSMs. On the other hand, the possibility of FDR estimation assisted by the plentiful non-top-scoring PSMs, which are almost always incorrect, has been scarcely explored. In this work, we propose a novel decoy-free procedure for developing null models for top-scoring PSMs using the transformed e-value (TEV) score and the distributions of non-top-scoring target PSMs. The method relies on a theoretically derivable relationship between the parameters of the distributions of lower-order statistics of the TEV score and a necessary empirical optimization to fit a single parameter to actual data. The framework was tested on multiple different data sets and two search engines. We present evidence that our method is comparable to and occasionally outperforms popular decoy-free and decoy-based methods in FDR estimation.

Proteomics profiling of vitreous humor reveals complement and coagulation components, adhesion factors, and neurodegeneration markers as discriminatory biomarkers of vitreoretinal eye diseases

Introduction

Diabetic retinopathy (DR) and age-related macular degeneration (AMD) are leading causes of visual impairment and blindness in people aged 50 years or older in middle-income and industrialized countries. Anti-VEGF therapies have improved the management of neovascular AMD (nAMD) and proliferative DR (PDR), no treatment options exist for the highly prevalent dry form of AMD.

Methods

To unravel the biological processes underlying these pathologies and to find new potential biomarkers, a label-free quantitative (LFQ) method was applied to analyze the vitreous proteome in PDR (n=4), AMD (n=4) compared to idiopathic epiretinal membranes (ERM) (n=4).

Results and discussion

Post-hoc tests revealed 96 proteins capable of differentiating among the different groups, whereas 118 proteins were found differentially regulated in PDR compared to ERM and 95 proteins in PDR compared to dry AMD. Pathway analysis indicates that mediators of complement, coagulation cascades and acute phase responses are enriched in PDR vitreous, whilst proteins highly correlated to the extracellular matrix (ECM) organization, platelet degranulation, lysosomal degradation, cell adhesion, and central nervous system development were found underexpressed. According to these results, 35 proteins were selected and monitored by MRM (multiple reaction monitoring) in a larger cohort of patients with ERM (n=21), DR/PDR (n=20), AMD (n=11), and retinal detachment (n=13). Of these, 26 proteins could differentiate between these vitreoretinal diseases. Based on Partial least squares discriminant and multivariate exploratory receiver operating characteristic (ROC) analyses, a panel of 15 discriminatory biomarkers was defined, which includes complement and coagulation components (complement C2 and prothrombin), acute-phase mediators (alpha-1-antichymotrypsin), adhesion molecules (e.g., myocilin, galectin-3-binding protein), ECM components (opticin), and neurodegeneration biomarkers (beta-amyloid, amyloid-like protein 2).

Unveiling the Links Between Peptide Identification and Differential Analysis FDR Controls by Means of a Practical Introduction to Knockoff Filters

In proteomic differential analysis, FDR control is often performed through a multiple test correction (i.e., the adjustment of the original p-values). In this protocol, we apply a recent and alternative method, based on so-called knockoff filters. It shares interesting conceptual similarities with the target-decoy competition procedure, classically used in proteomics for FDR control at peptide identification. To provide practitioners with a unified understanding of FDR control in proteomics, we apply the knockoff procedure on real and simulated quantitative datasets. Leveraging these comparisons, we propose to adapt the knockoff procedure to better fit the specificities of quantitative proteomic data (mainly very few samples). Performances of knockoff procedure are compared with those of the classical Benjamini-Hochberg procedure, hereby shedding a new light on the strengths and weaknesses of target-decoy competition.

Challenging Targets or Describing Mismatches? A Comment on Common Decoy Distribution by Madej et al

In their recent article, Madej et al. (Madej, D.; Wu, L.; Lam, H.Common Decoy Distributions Simplify False Discovery Rate Estimation in Shotgun Proteomics. J. Proteome Res.2022, 21 (2), 339-348) proposed an original way to solve the recurrent issue of controlling for the false discovery rate (FDR) in peptide-spectrum-match (PSM) validation. Briefly, they proposed to derive a single precise distribution of decoy matches termed the Common Decoy Distribution (CDD) and to use it to control for FDR during a target-only search. Conceptually, this approach is appealing as it takes the best of two worlds, i.e., decoy-based approaches (which leverage a large-scale collection of empirical mismatches) and decoy-free approaches (which are not subject to the randomness of decoy generation while sparing an additional database search). Interestingly, CDD also corresponds to a middle-of-the-road approach in statistics with respect to the two main families of FDR control procedures: Although historically based on estimating the false-positive distribution, FDR control has recently been demonstrated to be possible thanks to competition between the original variables (in proteomics, target sequences) and their fictional counterparts (in proteomics, decoys). Discriminating between these two theoretical trends is of prime importance for computational proteomics. In addition to highlighting why proteomics was a source of inspiration for theoretical biostatistics, it provides practical insights into the improvements that can be made to FDR control methods used in proteomics, including CDD.

Improving Peptide-Level Mass Spectrometry Analysis via Double Competition

The analysis of shotgun proteomics data often involves generating lists of inferred peptide-spectrum matches (PSMs) and/or of peptides. The canonical approach for generating these discovery lists is by controlling the false discovery rate (FDR), most commonly through target-decoy competition (TDC). At the PSM level, TDC is implemented by competing each spectrum's best-scoring target (real) peptide match with its best match against a decoy database. This PSM-level procedure can be adapted to the peptide level by selecting the top-scoring PSM per peptide prior to FDR estimation. Here, we first highlight and empirically augment a little known previous work by He et al., which showed that TDC-based PSM-level FDR estimates can be liberally biased. We thus propose that researchers instead focus on peptide-level analysis. We then investigate three ways to carry out peptide-level TDC and show that the most common method ("PSM-only") offers the lowest statistical power in practice. An alternative approach that carries out a double competition, first at the PSM and then at the peptide level ("PSM-and-peptide"), is the most powerful method, yielding an average increase of 17% more discovered peptides at 1% FDR threshold relative to the PSM-only method.

Elucidation of the interaction proteome of mitochondrial chaperone Hsp78 highlights its role in protein aggregation during heat stress

Chaperones of the Hsp100/Clp family represent major components of protein homeostasis, conferring maintenance of protein activity under stress. The ClpB-type members of the family, present in bacteria, fungi, and plants, are able to resolubilize aggregated proteins. The mitochondrial member of the ClpB family in Saccharomyces cerevisiae is Hsp78. Although Hsp78 has been shown to contribute to proteostasis in elevated temperatures, the biochemical mechanisms underlying this mitochondria-specific thermotolerance are still largely unclear. To identify endogenous chaperone substrate proteins, here, we generated an Hsp78-ATPase mutant with stabilized substrate-binding behavior. We used two stable isotope labeling–based quantitative mass spectrometry approaches to analyze the role of Hsp78 during heat stress–induced mitochondrial protein aggregation and disaggregation on a proteomic level. We first identified the endogenous substrate spectrum of the Hsp78 chaperone, comprising a wide variety of proteins related to metabolic functions including energy production and protein synthesis, as well as other chaperones, indicating its crucial functions in mitochondrial stress resistance. We then compared these interaction data with aggregation and disaggregation processes in mitochondria under heat stress, which revealed specific aggregation-prone protein populations and demonstrated the direct quantitative impact of Hsp78 on stress-dependent protein solubility under different conditions. We conclude that Hsp78, together with its cofactors, represents a recovery system that protects major mitochondrial metabolic functions during heat stress as well as restores protein biogenesis capacity after the return to normal conditions.

Integrated Profiling of Gram-Positive and Gram-Negative Probiotic Genomes, Proteomes and Metabolomes Revealed Small Molecules with Differential Growth Inhibition of Antimicrobial-Resistant Pathogens

Probiotics produce small molecules that may serve as alternatives to conventional antibiotics by suppressing growth of antimicrobial resistant (AMR) pathogens. The objective of this study was to identify and examine antimicrobials produced and secreted by probiotics using 'omics' profiling with computer-based metabolic flux analyses. The cell-free supernatant of Gram-positive Lacticaseibacillus rhamnosus GG (LGG) and Gram-negative Escherichia coli Nissle (ECN) probiotics inhibited growth of AMR Salmonella Typhimurium, Escherichia coli, and Klebsiella oxytoca ranging between 28.85 - 41.20% (LGG) and 11.48 - 29.45% (ECN). A dose dependent analysis of probiotic supernatants showed LGG was 6.27% to 20.55% more effective at reducing AMR pathogen growth when compared to ECN. Principal component analysis showed clear separation of ECN and LGG cell free supernatant metabolomes. Among 667 metabolites in the supernatant, 304 were differentially abundant between LGG and ECN probiotics. Proteomics identified 87 proteins, whereby 67 (ECN) and 14 (LGG) showed differential expression as enzymes related to carbohydrate and energy metabolic pathways. The whole genomes and metabolomes were next used for in-silico metabolic network analysis. The model predicted the production of 166 metabolites by LGG and ECN probiotics across amino acid, carbohydrate/energy, and nucleotide metabolism with antimicrobial functions. The predictive accuracy of the metabolic flux analysis highlights the novel utility for profiling probiotic supplements as dietary-based antimicrobial alternatives in the control of AMR pathogen growth.

Protease Inhibitors from Solanum chacoense Inhibit Pectobacterium Virulence by Reducing Bacterial Protease Activity and Motility

Potato is a major staple crop, and necrotrophic bacterial pathogens such as Pectobacterium spp. are a major threat to global food security. Most lines of cultivated potato (Solanum tuberosum) are susceptible to Pectobacterium spp., but some lines of wild potato are resistant, including Solanum chacoense M6. Despite the discovery of resistance in wild potatoes, specific resistance genes are yet to be discovered. Crude protein extract from M6 had a global effect on Pectobacterium brasiliense Pb1692 (Pb1692) virulence phenotypes. Specifically, M6 protein extracts resulted in reduced Pectobacterium exo-protease activity and motility, induced cell elongation, and affected bacterial virulence and metabolic gene expression. These effects were not observed from protein extracts of susceptible potato S. tuberosum DM1. A proteomics approach identified protease inhibitors (PIs) as candidates for S. chacoense resistance, and genomic analysis showed higher abundance and diversity of PIs in M6 than in DM1. We cloned five PIs that are unique or had high abundance in M6 compared with DM1 and purified the proteins (g18987, g28531, g39249, g40384, g6571). Four of the PIs significantly reduced bacterial protease activity, with strongest effects from g28531 and g6571. Three PIs (g18987, g28531, g6571) inhibited disease when co-inoculated with Pectobacterium pathogens into potato tubers. Two PIs (g28531, g6571) also significantly reduced Pb1692 motility and are promising as resistance genes. These results show that S. chacoense PIs contribute to bacterial disease resistance by inhibiting exo-proteases, motility, and tuber maceration and by modulating cell morphology and metabolism. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Proteomic Analysis of Methanococcus voltae Grown in the Presence of Mineral and Nonmineral Sources of Iron and Sulfur

Iron sulfur (Fe-S) proteins are essential and ubiquitous across all domains of life, yet the mechanisms underpinning assimilation of iron (Fe) and sulfur (S) and biogenesis of Fe-S clusters are poorly understood. This is particularly true for anaerobic methanogenic archaea, which are known to employ more Fe-S proteins than other prokaryotes. Here, we utilized a deep proteomics analysis of Methanococcus voltae A3 cultured in the presence of either synthetic pyrite (FeS2) or aqueous forms of ferrous iron and sulfide to elucidate physiological responses to growth on mineral or nonmineral sources of Fe and S. The liquid chromatography-mass spectrometry (LCMS) shotgun proteomics analysis included 77% of the predicted proteome. Through a comparative analysis of intra- and extracellular proteomes, candidate proteins associated with FeS2 reductive dissolution, Fe and S acquisition, and the subsequent transport, trafficking, and storage of Fe and S were identified. The proteomic response shows a large and balanced change, suggesting that M. voltae makes physiological adjustments involving a range of biochemical processes based on the available nutrient source. Among the proteins differentially regulated were members of core methanogenesis, oxidoreductases, membrane proteins putatively involved in transport, Fe-S binding ferredoxin and radical S-adenosylmethionine proteins, ribosomal proteins, and intracellular proteins involved in Fe-S cluster assembly and storage. This work improves our understanding of ancient biogeochemical processes and can support efforts in biomining of minerals. IMPORTANCE Clusters of iron and sulfur are key components of the active sites of enzymes that facilitate microbial conversion of light or electrical energy into chemical bonds. The proteins responsible for transporting iron and sulfur into cells and assembling these elements into metal clusters are not well understood. Using a microorganism that has an unusually high demand for iron and sulfur, we conducted a global investigation of cellular proteins and how they change based on the mineral forms of iron and sulfur. Understanding this process will answer questions about life on early earth and has application in biomining and sustainable sources of energy.

Methods to capture proteomic and metabolomic signatures from cerebrospinal fluid and serum of healthy individuals

Discovery of reliable signatures for the empirical diagnosis of neurological diseases-both infectious and non-infectious-remains unrealized. One of the primary challenges encountered in such studies is the lack of a comprehensive database representative of a signature background that exists in healthy individuals, and against which an aberrant event can be assessed. For neurological insults and injuries, it is important to understand the normal profile in the neuronal (cerebrospinal fluid) and systemic fluids (e.g., blood). Here, we present the first comparative multi-omic human database of signatures derived from a population of 30 individuals (15 males, 15 females, 23-74 years) of serum and cerebrospinal fluid. In addition to empirical signatures, we also assigned common pathways between serum and CSF. Together, our findings provide a cohort against which aberrant signature profiles in individuals with neurological injuries/disease can be assessed-providing a pathway for comprehensive diagnostics and therapeutics discovery.

Rapid and in-depth coverage of the (phospho-)proteome with deep libraries and optimal window design for dia-PASEF

Data-independent acquisition (DIA) methods have become increasingly attractive in mass spectrometry–based proteomics because they enable high data completeness and a wide dynamic range. Recently, we combined DIA with parallel accumulation–serial fragmentation (dia-PASEF) on a Bruker trapped ion mobility (IM) separated quadrupole time-of-flight mass spectrometer. This requires alignment of the IM separation with the downstream mass selective quadrupole, leading to a more complex scheme for dia-PASEF window placement compared with DIA. To achieve high data completeness and deep proteome coverage, here we employ variable isolation windows that are placed optimally depending on precursor density in the m/z and IM plane. This is implemented in the freely available py_diAID (Python package for DIA with an automated isolation design) package. In combination with in-depth project-specific proteomics libraries and the Evosep liquid chromatography system, we reproducibly identified over 7700 proteins in a human cancer cell line in 44 min with quadruplicate single-shot injections at high sensitivity. Even at a throughput of 100 samples per day (11 min liquid chromatography gradients), we consistently quantified more than 6000 proteins in mammalian cell lysates by injecting four replicates. We found that optimal dia-PASEF window placement facilitates in-depth phosphoproteomics with very high sensitivity, quantifying more than 35,000 phosphosites in a human cancer cell line stimulated with an epidermal growth factor in triplicate 21 min runs. This covers a substantial part of the regulated phosphoproteome with high sensitivity, opening up for extensive systems-biological studies.

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Optimal dia-PASEF window design with py_diAID combined with deep libraries.

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Quantification of the HeLa cell proteome to a depth of >7700 in only 44 min.

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Ion mobility–resolved phosphoproteomics determines >35,000 class I phosphosites.

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py_diAID is freely available as GUI, CLI, and Python modules.

Tandem mass tag labeling to assess proteome differences between intermediate and very tender beef steaks

Tenderness is considered as one of the most important quality attributes dictating consumers' overall satisfaction and future purchasing decisions of fresh beef. However, the ability to predict and manage tenderness has proven very challenging due to the numerous factors that contribute to variation in end-product tenderness. Proteomic profiling allows for global examination of differentially abundant proteins in the meat and can provide new insight into biological mechanisms related to meat tenderness. Hence, the objective of this study was to examine proteomic profiles of beef longissimus lumborum (LL) steaks varying in tenderness, with the intention to identify potential biomarkers related to tenderness. For this purpose, beef LL muscle samples were collected from 99 carcasses at 0 and 384 h postmortem. Based on Warner-Bratzler shear force values at 384 h, 16 samples with the highest (intermediate tender, IT) and lowest (very tender, VT) values were selected to be used for proteomic analysis in this study (n = 8 per category). Using tandem mass tag-based proteomics, a total of 876 proteins were identified, of which 51 proteins were differentially abundant (P < 0.05) between the tenderness categories and aging periods. The differentially identified proteins encompassed a wide array of biological processes related to muscle contraction, calcium signaling, metabolism, extracellular matrix organization, chaperone, and apoptosis. A greater (P < 0.05) relative abundance of proteins associated with carbohydrate metabolism and apoptosis, and a lower (P < 0.05) relative abundance of proteins involved in muscle contraction was observed in the VT steaks after aging compared with the IT steaks, suggesting that more proteolysis occurred in the VT steaks. This may be explained by the greater (P < 0.05) abundance of chaperonin and calcium-binding proteins in the IT steaks, which could have limited the extent of postmortem proteolysis in these steaks. In addition, a greater (P < 0.05) abundance of connective tissue proteins was also observed in the IT steaks, which likely contributed to the difference in tenderness due to added background toughness. The established proteomic database obtained in this study may provide a reference for future research regarding potential protein biomarkers that are associated with meat tenderness.

dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts

The dia-PASEF technology uses ion mobility separation to reduce signal interferences and increase sensitivity in proteomic experiments. Here we present a two-dimensional peak-picking algorithm and generation of optimized spectral libraries, as well as take advantage of neural network-based processing of dia-PASEF data. Our computational platform boosts proteomic depth by up to 83% compared to previous work, and is specifically beneficial for fast proteomic experiments and those with low sample amounts. It quantifies over 5300 proteins in single injections recorded at 200 samples per day throughput using Evosep One chromatography system on a timsTOF Pro mass spectrometer and almost 9000 proteins in single injections recorded with a 93-min nanoflow gradient on timsTOF Pro 2, from 200 ng of HeLa peptides. A user-friendly implementation is provided through the incorporation of the algorithms in the DIA-NN software and by the FragPipe workflow for spectral library generation.

Sequence, structure, and function of the Dps DNA-binding protein from Deinococcus wulumuqiensis R12

Deinococcus wulumuqiensis R12, which was isolated from arid irradiated soil in Xinjiang province of China, belongs to a genus that is well-known for its extreme resistance to ionizing radiation and oxidative stress. The DNA-binding protein Dps has been studied for its great contribution to oxidative resistance. To explore the role of Dps in D. wulumuqiensis R12, the Dps sequence and homology-modeled structure were analyzed. In addition, the dps gene was knocked out and proteomics was used to verify the functions of Dps in D. wulumuqiensis R12. Docking data and DNA binding experiments in vitro showed that the R12 Dps protein has a better DNA binding ability than the Dps1 protein from D. radiodurans R1. When the dps gene was deleted in D. wulumuqiensis R12, its resistance to H₂O₂ and UV rays was greatly reduced, and the cell envelope was destroyed by H₂O₂ treatment. Additionally, the qRT-PCR and proteomics data suggested that when the dps gene was deleted, the catalase gene was significantly down-regulated. The proteomics data indicated that the metabolism, transport and oxidation–reduction processes of D. wulumuqiensis R12 were down-regulated after the deletion of the dps gene. Overall, the data conformed that Dps protein plays an important role in D. wulumuqiensis R12.

Loss of Prm1 leads to defective chromatin protamination, impaired PRM2 processing, reduced sperm motility and subfertility in male mice

One of the key events during spermiogenesis is the hypercondensation of chromatin by substitution of the majority of histones by protamines. In humans and mice, protamine 1 (PRM1/Prm1) and protamine 2 (PRM2/Prm2) are expressed in a species-specific ratio. Using CRISPR-Cas9-mediated gene editing, we generated Prm1-deficient mice and demonstrated that Prm1+/- mice were subfertile, whereas Prm1-/- mice were infertile. Prm1-/- and Prm2-/- sperm showed high levels of reactive oxygen species-mediated DNA damage and increased histone retention. In contrast, Prm1+/- sperm displayed only moderate DNA damage. The majority of Prm1+/- sperm were CMA3 positive, indicating protamine-deficient chromatin, although this was not the result of increased histone retention in Prm1+/- sperm. However, sperm from Prm1+/- and Prm1-/- mice contained high levels of incompletely processed PRM2. Furthermore, the PRM1:PRM2 ratio was skewed from 1:2 in wild type to 1:5 in Prm1+/- animals. Our results reveal that PRM1 is required for proper PRM2 processing to produce mature PRM2, which, together with PRM1, is able to hypercondense DNA. Thus, the species-specific PRM1:PRM2 ratio has to be precisely controlled in order to retain full fertility.

Loss of the cleaved-protamine 2 domain leads to incomplete histone-to-protamine exchange and infertility in mice

Protamines are unique sperm-specific proteins that package and protect paternal chromatin until fertilization. A subset of mammalian species expresses two protamines (PRM1 and PRM2), while in others PRM1 is sufficient for sperm chromatin packaging. Alterations of the species-specific ratio between PRM1 and PRM2 are associated with infertility. Unlike PRM1, PRM2 is generated as a precursor protein consisting of a highly conserved N-terminal domain, termed cleaved PRM2 (cP2), which is consecutively trimmed off during chromatin condensation. The carboxyterminal part, called mature PRM2 (mP2), interacts with DNA and together with PRM1, mediates chromatin-hypercondensation. The removal of the cP2 domain is believed to be imperative for proper chromatin condensation, yet, the role of cP2 is not yet understood. We generated mice lacking the cP2 domain while the mP2 is still expressed. We show that the cP2 domain is indispensable for complete sperm chromatin protamination and male mouse fertility. cP2 deficient sperm show incomplete protamine incorporation and a severely altered protamine ratio, retention of transition proteins and aberrant retention of the testis specific histone variant H2A.L.2. During epididymal transit, cP2 deficient sperm seem to undergo ROS mediated degradation leading to complete DNA fragmentation. The cP2 domain therefore seems to be a key aspect in the complex crosstalk between histones, transition proteins and protamines during sperm chromatin condensation. Overall, we present the first step towards understanding the role of the cP2 domain in paternal chromatin packaging and open up avenues for further research.

Protamines are small sperm-specific proteins crucial to packaging and protecting the paternal genome on its way to the fertilization site. Most mammalian species express only protamine 1. However, primates and rodents additionally express protamine 2. Protamine 2 differs mainly in its N-terminal domain (cP2), which is sequentially cleaved off during paternal chromatin packaging. Alteration in this process has been associated with infertility. However, the precise role of cP2 is still a mystery. We generated cP2 deficient mice and demonstrate, that loss of cP2 results in incomplete histone-to-protamine transition, resulting in sperm DNA degradation and infertility. Evidently, cP2 helps in orchestrating the fine-tuned dynamics of DNA-hypercondensation while protecting DNA integrity and aiding removal of DNA-bound transition proteins.

Comparing Efficiency of Lysis Buffer Solutions and Sample Preparation Methods for Liquid Chromatography-Mass Spectrometry Analysis of Human Cells and Plasma

The use of a proper sample processing methodology for maximum proteome coverage and high-quality quantitative data is an important choice to make before initiating a liquid chromatography–mass spectrometry (LC–MS)-based proteomics study. Popular sample processing workflows for proteomics involve in-solution proteome digestion and single-pot, solid-phase-enhanced sample preparation (SP3). We tested them on both HeLa cells and human plasma samples, using lysis buffers containing SDS, or guanidinium hydrochloride. We also studied the effect of using commercially available depletion mini spin columns before SP3, to increase proteome coverage in human plasma samples. Our results show that the SP3 protocol, using either buffer, achieves the highest number of quantified proteins in both the HeLa cells and plasma samples. Moreover, the use of depletion mini spin columns before SP3 results in a two-fold increase of quantified plasma proteins. With additional fractionation, we quantified nearly 1400 proteins, and examined lower-abundance proteins involved in neurodegenerative pathways and mitochondrial metabolism. Therefore, we recommend the use of the SP3 methodology for biological sample processing, including those after depletion of high-abundance plasma proteins.

Definition of germ layer cell lineage alternative splicing programs reveals a critical role for Quaking in specifying cardiac cell fate

Alternative splicing is critical for development; however, its role in the specification of the three embryonic germ layers is poorly understood. By performing RNA-Seq on human embryonic stem cells (hESCs) and derived definitive endoderm, cardiac mesoderm, and ectoderm cell lineages, we detect distinct alternative splicing programs associated with each lineage. The most prominent splicing program differences are observed between definitive endoderm and cardiac mesoderm. Integrative multi-omics analyses link each program with lineage-enriched RNA binding protein regulators, and further suggest a widespread role for Quaking (QKI) in the specification of cardiac mesoderm. Remarkably, knockout of QKI disrupts the cardiac mesoderm-associated alternative splicing program and formation of myocytes. These changes arise in part through reduced expression of BIN1 splice variants linked to cardiac development. Mechanistically, we find that QKI represses inclusion of exon 7 in BIN1 pre-mRNA via an exonic ACUAA motif, and this is concomitant with intron removal and cleavage from chromatin. Collectively, our results uncover alternative splicing programs associated with the three germ lineages and demonstrate an important role for QKI in the formation of cardiac mesoderm.

Proteomic Characterization of the Oral Pathogen Filifactor alocis Reveals Key Inter-Protein Interactions of Its RTX Toxin: FtxA

Filifactor alocis is a Gram-positive asaccharolytic, obligate anaerobic rod that has been isolated from a variety of oral infections including periodontitis, peri-implantitis, and odontogenic abscesses. As a newly emerging pathogen, its type strain has been investigated for pathogenic properties, yet little is known about its virulence variations among strains. We previously screened the whole genome of nine clinical oral isolates and a reference strain of F. alocis, and they expressed a novel RTX toxin, FtxA. In the present study, we aimed to use label-free quantification proteomics to characterize the full proteome of those ten F. alocis strains. A total of 872 proteins were quantified, and 97 among them were differentially expressed in FtxA-positive strains compared with the negative strains. In addition, 44 of these differentially expressed proteins formed 66 pairs of associations based on their predicted functions, which included clusters of proteins with DNA repair/mediated transformation and catalytic activity-related function, indicating different biosynthetic activities among strains. FtxA displayed specific interactions with another six intracellular proteins, forming a functional cluster that could discriminate between FtxA-producing and non-producing strains. Among them were FtxB and FtxD, predicted to be encoded by the same operon as FtxA. While revealing the broader qualitative and quantitative proteomic landscape of F. alocis, this study also sheds light on the deeper functional inter-relationships of FtxA, thus placing this RTX family member into context as a major virulence factor of this species.

False discovery rate: the Achilles' heel of proteogenomics

Proteogenomics refers to the integrated analysis of the genome and proteome that leverages mass-spectrometry (MS)-based proteomics data to improve genome annotations, understand gene expression control through proteoforms and find sequence variants to develop novel insights for disease classification and therapeutic strategies. However, proteogenomic studies often suffer from reduced sensitivity and specificity due to inflated database size. To control the error rates, proteogenomics depends on the target-decoy search strategy, the de-facto method for false discovery rate (FDR) estimation in proteomics. The proteogenomic databases constructed from three- or six-frame nucleotide database translation not only increase the search space and compute-time but also violate the equivalence of target and decoy databases. These searches result in poorer separation between target and decoy scores, leading to stringent FDR thresholds. Understanding these factors and applying modified strategies such as two-pass database search or peptide-class-specific FDR can result in a better interpretation of MS data without introducing additional statistical biases. Based on these considerations, a user can interpret the proteogenomics results appropriately and control false positives and negatives in a more informed manner. In this review, first, we briefly discuss the proteogenomic workflows and limitations in database construction, followed by various considerations that can influence potential novel discoveries in a proteogenomic study. We conclude with suggestions to counter these challenges for better proteogenomic data interpretation.

Tandem Mass Spectrometry-Based Amyloid Typing Using Manual Microdissection and Open-Source Data Processing

OBJECTIVES

Standard implementations of amyloid typing by liquid chromatography-tandem mass spectrometry use capabilities unavailable to most clinical laboratories. To improve accessibility of this testing, we explored easier approaches to tissue sampling and data processing.

METHODS

We validated a typing method using manual sampling in place of laser microdissection, pairing the technique with a semiquantitative measure of sampling adequacy. In addition, we created an open-source data processing workflow (Crux Pipeline) for clinical users.

RESULTS

Cases of amyloidosis spanning the major types were distinguishable with 100% specificity using measurements of individual amyloidogenic proteins or in combination with the ratio of λ and κ constant regions. Crux Pipeline allowed for rapid, batched data processing, integrating the steps of peptide identification, statistical confidence estimation, and label-free protein quantification.

CONCLUSIONS

Accurate mass spectrometry-based amyloid typing is possible without laser microdissection. To facilitate entry into solid tissue proteomics, newcomers can leverage manual sampling approaches in combination with Crux Pipeline and related tools.

Pytheas: a software package for the automated analysis of RNA sequences and modifications via tandem mass spectrometry

Mass spectrometry is an important method for analysis of modified nucleosides ubiquitously present in cellular RNAs, in particular for ribosomal and transfer RNAs that play crucial roles in mRNA translation and decoding. Furthermore, modifications have effect on the lifetimes of nucleic acids in plasma and cells and are consequently incorporated into RNA therapeutics. To provide an analytical tool for sequence characterization of modified RNAs, we developed Pytheas, an open-source software package for automated analysis of tandem MS data for RNA. The main features of Pytheas are flexible handling of isotope labeling and RNA modifications, with false discovery rate statistical validation based on sequence decoys. We demonstrate bottom-up mass spectrometry characterization of diverse RNA sequences, with broad applications in the biology of stable RNAs, and quality control of RNA therapeutics and mRNA vaccines.

Integrative description of changes occurring on zebrafish embryos exposed to water-soluble crude oil components and its mixture with a chemical surfactant

The effects of crude oil spills are an ongoing problem for wildlife and human health in both marine and freshwater aquatic environments. Bioassays of model organisms are a convenient way to assess the potential risks of the substances involved in oil spills. Zebrafish embryos (ZFE) are a useful to reach a fast and detailed description of the toxicity of the pollutants, including both the components of the crude oil itself and substances that are commonly used for crude oil spill mitigation (e.g. surfactants). Here, we evaluated the survival rate, as well as histological, morphological, and proteomic changes in ZFE exposed to Water Accumulated Fraction (WAF) of light crude oil and in mixture with dioctyl sulfosuccinate sodium (DOSS, e.g. CEWAF: Chemically Enhanced WAF), a surfactant that is frequently used in chemical dispersant formulations. Furthermore, we compared de hydrocarbon concentration of WAF and CEWAF of the sublethal dilution. In histological, morphological, and gene expression variables, the ZFE exposed to WAF showed less changes than those exposed to CEWAF. Proteomic changes were more dramatic in ZFE exposed to WAF, with important alterations in spliceosomal and ribosomal proteins, as well as proteins related to eye and retinal photoreceptor development and heart function. We also found that the concentration of high molecular weight hydrocarbons in water was slighly higher in presence of DOSS, but the low molecular weight hydrocarbons concentration was higher in WAF. These results provide an important starting point for identifying useful crude-oil exposure biomarkers in fish species.