Simple, efficient and thorough shotgun proteomic analysis with PatternLab V

Integrating DIA Single-Cell Proteomics Data with the DiagnoMass Proteomic Hub for Biological Insights

Single-cell proteomics has emerged as a powerful technology for unraveling the complexities of cellular heterogeneity, enabling insights into individual cell functions and pathologies. One of the primary challenges in single-cell proteomics is data generation, where low mass spectral signals often preclude the triggering of MS2 events. This challenge is addressed by Data Independent Acquisition (DIA), a data acquisition strategy that does not depend on peptide ion isotopic signatures to generate an MS2 event. In this study, we present data generated from the integration of DIA single-cell proteomics with a version of the DiagnoMass Proteomic Hub that was adapted to handle DIA data. DiagnoMass employs a hierarchical clustering methodology that enables the identification of tandem mass spectral clusters that are discriminative of biological conditions, thereby reducing the reliance on search engine biases for identifications. Nevertheless, a search engine (in this work, DIA-NN) can be integrated with DiagnoMass for spectral annotation. We used single-cell proteomic data from iPSC-derived neuroprogenitor cell cultures as a test study of this integrated approach. We were able to differentiate between control and Rett Syndrome patient cells to discern the proteomic variances potentially contributing to the disease's pathology. Our research confirms that the DiagnoMass-DIA synergy significantly enhances the identification of discriminative proteomic signatures, highlighting critical biological variations such as the presence of unique spectra that could be related to Rett Syndrome pathology.

OmicScope unravels systems-level insights from quantitative proteomics data

Shotgun proteomics analysis presents multifaceted challenges, demanding diverse tool integration for insights. Addressing this complexity, OmicScope emerges as an innovative solution for quantitative proteomics data analysis. Engineered to handle various data formats, it performs data pre-processing - including joining replicates, normalization, data imputation - and conducts differential proteomics analysis for both static and longitudinal experimental designs. Empowered by Enrichr with over 224 databases, OmicScope performs Over Representation Analysis (ORA) and Gene Set Enrichment Analysis (GSEA). Additionally, its Nebula module facilitates meta-analysis from independent datasets, providing a systems biology approach for enriched insights. Complete with a data visualization toolkit and accessible as Python package and a web application, OmicScope democratizes proteomics analysis, offering an efficient and high-quality pipeline for researchers.

RawVegetable 2.0: Refining XL-MS Data Acquisition through Enhanced Quality Control

We present RawVegetable 2.0, a software tailored for assessing mass spectrometry data quality and fine-tuned for cross-linking mass spectrometry (XL-MS) applications. Building upon the capabilities of its predecessor, RawVegetable 2.0 introduces four main modules, each providing distinct and new functionalities: 1) Pair Finder, which identifies ion doublets characteristic of cleavable cross-linking experiments; 2) Diagnostic Peak Finder, which locates potential reporter ions associated with a specific cross-linker; 3) Precursor Signal Ratio, which computes the ratio between precursor intensity and the total signal in an MS/MS scan; and 4) Xrea, which evaluates spectral quality by analyzing the heterogeneity of peak intensities within a spectrum. These modules collectively streamline the process of optimizing mass spectrometry data acquisition for both Proteomics and XL-MS experiments. RawVegetable 2.0, along with a comprehensive tutorial is freely accessible for academic use at: http://patternlabforproteomics.org/rawvegetable2.

Kinetics characterization of a low immunogenic recombinant l-asparaginase from Phaseolus vulgaris with cytotoxic activity against leukemia cells

l-asparaginases play a crucial role in the treatment of acute lymphoblastic leukemia (ALL), a type of cancer that mostly affects children and teenagers. However, it is common for these molecules to cause adverse reactions during treatment. These downsides ignite the search for novel asparaginases to mitigate these problems. Thus, this work aimed to produce and characterize a recombinant asparaginase from Phaseolus vulgaris (Asp-P). In this study, Asp-P was expressed in Escherichia coli with high yields and optimum activity at 40 °C, pH 9.0. The enzyme Km and Vmax values were 7.05 mM and 1027 U/mg, respectively. Asp-P is specific for l-asparagine, showing no activity against l-glutamine and other amino acids. The enzyme showed a higher cytotoxic effect against Raji than K562 cell lines, but only at high concentrations. In silico analysis indicated that Asp-P has lower immunogenicity than a commercial enzyme. Asp-P induced biofilm formation by Candida sp. due to sublethal dose, showing an underexplored potential of asparaginases. The absence of glutaminase activity, lower immunogenicity and optimal activity similar to physiological temperature conditions are characteristics that indicate Asp-P as a potential new commercial enzyme in the treatment of ALL and its underexplored application in the treatment of other diseases.

Intra-Individual Paired Mass Spectrometry Dataset for Decoding Solar-Induced Proteomic Changes in Facial Skin

Photoaging is the premature aging of the skin caused by prolonged exposure to solar radiation. The visual alterations manifest as wrinkles, reduced skin elasticity, uneven skin tone, as well as other signs that surpass the expected outcomes of natural aging. Beyond these surface changes, there is a complex interplay of molecular alterations, encompassing shifts in cellular function, DNA damage, and protein composition disruptions. This data descriptor introduces a unique dataset derived from ten individuals, each with a minimum of 18 years of professional experience as a driver, who are asymmetrically and chronically exposed to solar radiation due to their driving orientation. Skin samples were independently collected from each side of the face using a microdermabrasion-like procedure and analyzed on an Exploris 240 mass spectrometer. Our adapted proteomic statistical framework leverages the sample pairing to provide robust insights. This dataset delves into the molecular differences in exposed skin and serves as a foundational resource for interdisciplinary research in photodermatology, targeted skincare treatments, and computational modelling of skin health.

A Module for Analyzing Interactomes via APEX-MS Integrated into PatternLab for Proteomics

Proximity labeling techniques, such as APEX-MS, provide valuable insights into proximal interactome mapping; however, the verification of biotinylated peptides is not straightforward. With this as motivation, we present a new module integrated into PatternLab for proteomics to enable APEX-MS data interpretation by targeting diagnostic fragment ions associated with APEX modifications. We reanalyzed a previously published APEX-MS data set and report a significant number of biotinylated peptides and, consequently, a confident set of proximal proteins. As the module is part of the widely adopted PatternLab for proteomics software suite, it offers users a comprehensive, easy, and integrated solution for data analysis. Given the broad utility of the APEX-MS technique in various biological contexts, we anticipate that our module will be a valuable asset to researchers, facilitating and enhancing interactome studies. PatternLab's APEX, including a usage protocol, is available at http://patternlabforproteomics.org/apex.

Proteomics reveals that the antifungal activity of fenbendazole against Cryptococcus neoformans requires protein kinases

Cryptococcus neoformans is responsible for over 100 000 deaths annually, and the treatment of this fungal disease is expensive and not consistently effective. Unveiling new therapeutic avenues is crucial. Previous studies have suggested that the anthelmintic drug fenbendazole is an affordable and nontoxic candidate to combat cryptococcosis. However, its mechanism of anticryptococcal activity has been only superficially investigated. In this study, we examined the global cellular response of C. neoformans to fenbendazole using a proteomic approach (data are available via ProteomeXchange with identifier PXD047041). Fenbendazole treatment mostly impacted the abundance of proteins related to metabolic pathways, RNA processing, and intracellular traffic. Protein kinases, in particular, were significantly affected by fenbendazole treatment. Experimental validation of the proteomics data using a collection of C. neoformans mutants led to the identification of critical roles of five protein kinases in fenbendazole's antifungal activity. In fact, mutants lacking the expression of genes encoding Chk1, Tco2, Tco3, Bub1, and Sch9 kinases demonstrated greater resistance to fenbendazole compared to wild-type cells. In combination with the standard antifungal drug amphotericin B, fenbendazole reduced the cryptococcal burden in mice. These findings not only contribute to the elucidation of fenbendazole's mode of action but also support its use in combination therapy with amphotericin B. In conclusion, our data suggest that fenbendazole holds promise for further development as an anticryptococcal agent.

Corrected and republished from: "Extracellular Vesicle Formation in Cryptococcus deuterogattii Impacts Fungal Virulence"

Small molecules are components of fungal extracellular vesicles (EVs), but their biological roles are only superficially known. NOP16 is a eukaryotic gene that is required for the activity of benzimidazoles against Cryptococcus deuterogattii. In this study, during the phenotypic characterization of C. deuterogattii mutants expected to lack NOP16 expression, we observed a reduced EV production. Whole-genome sequencing, RNA-Seq, and cellular proteomics revealed that, contrary to our initial findings, these mutants expressed Nop16 but exhibited altered expression of 14 genes potentially involved in sugar transport. Based on this observation, we designated these mutant strains as Past1 and Past2, representing potentially altered sugar transport. Analysis of the small molecule composition of EVs produced by wild-type cells and the Past1 and Past2 mutant strains revealed not only a reduced number of EVs but also an altered small molecule composition. In a Galleria mellonella model of infection, the Past1 and Past2 mutant strains were hypovirulent. The hypovirulent phenotype was reverted when EVs produced by wild-type cells, but not mutant EVs, were co-injected with the mutant cells in G. mellonella. These results connect EV biogenesis, cargo, and cryptococcal virulence.

Key Proteomics Tools for Fundamental and Applied Microalgal Research

Microscopic, photosynthetic prokaryotes and eukaryotes, collectively referred to as microalgae, are widely studied to improve our understanding of key metabolic pathways (e.g., photosynthesis) and for the development of biotechnological applications. Omics technologies, which are now common tools in biological research, have been shown to be critical in microalgal research. In the past decade, significant technological advancements have allowed omics technologies to become more affordable and efficient, with huge datasets being generated. In particular, where studies focused on a single or few proteins decades ago, it is now possible to study the whole proteome of a microalgae. The development of mass spectrometry-based methods has provided this leap forward with the high-throughput identification and quantification of proteins. This review specifically provides an overview of the use of proteomics in fundamental (e.g., photosynthesis) and applied (e.g., lipid production for biofuel) microalgal research, and presents future research directions in this field.

Urinary proteomics reveals biological processes related to acute kidney injury in Bothrops atrox envenomings

Acute kidney injury (AKI) is a critical systemic complication caused by Bothrops envenoming, a neglected health problem in the Brazilian Amazon. Understanding the underlying mechanisms leading to AKI is crucial for effectively mitigating the burden of this complication. This study aimed to characterize the urinary protein profile of Bothrops atrox snakebite victims who developed AKI. We analyzed three groups of samples collected on admission: healthy subjects (controls, n = 10), snakebite victims who developed AKI (AKI, n = 10), and those who did not evolve to AKI (No-AKI, n = 10). Using liquid-chromatography tandem mass spectrometry, we identified and quantified (label-free) 1190 proteins. A panel of 65 proteins was identified exclusively in the urine of snakebite victims, with 32 exclusives to the AKI condition. Proteins more abundant or exclusive in AKI's urine were associated with acute phase response, endopeptidase inhibition, complement cascade, and inflammation. Notable proteins include serotransferrin, SERPINA-1, alpha-1B-glycoprotein, and NHL repeat-containing protein 3. Furthermore, evaluating previously reported biomarkers candidates for AKI and renal injury, we found retinol-binding protein, beta-2-microglobulin, cystatin-C, and hepcidin to be significant in cases of AKI induced by Bothrops envenoming. This work sheds light on physiological disturbances caused by Bothrops envenoming, highlighting potential biological processes contributing to AKI. Such insights may aid in better understanding and managing this life-threatening complication.

Proteomic Analysis of a Rat Streptozotocin Model Shows Dysregulated Biological Pathways Implicated in Alzheimer's Disease

Alzheimer's Disease (AD) is an age-related neurodegenerative disorder characterized by progressive memory loss and cognitive impairment, affecting 35 million individuals worldwide. Intracerebroventricular (ICV) injection of low to moderate doses of streptozotocin (STZ) in adult male Wistar rats can reproduce classical physiopathological hallmarks of AD. This biological model is known as ICV-STZ. Most studies are focused on the description of behavioral and morphological aspects of the ICV-STZ model. However, knowledge regarding the molecular aspects of the ICV-STZ model is still incipient. Therefore, this work is a first attempt to provide a wide proteome description of the ICV-STZ model based on mass spectrometry (MS). To achieve that, samples from the pre-frontal cortex (PFC) and hippocampus (HPC) of the ICV-STZ model and control (wild-type) were used. Differential protein abundance, pathway, and network analysis were performed based on the protein identification and quantification of the samples. Our analysis revealed dysregulated biological pathways implicated in the early stages of late-onset Alzheimer's disease (LOAD), based on differentially abundant proteins (DAPs). Some of these DAPs had their mRNA expression further investigated through qRT-PCR. Our results shed light on the AD onset and demonstrate the ICV-STZ as a valid model for LOAD proteome description.

SpliceProt 2.0: A Sequence Repository of Human, Mouse, and Rat Proteoforms

SpliceProt 2.0 is a public proteogenomics database that aims to list the sequence of known proteins and potential new proteoforms in human, mouse, and rat proteomes. This updated repository provides an even broader range of computationally translated proteins and serves, for example, to aid with proteomic validation of splice variants absent from the reference UniProtKB/SwissProt database. We demonstrate the value of SpliceProt 2.0 to predict orthologous proteins between humans and murines based on transcript reconstruction, sequence annotation and detection at the transcriptome and proteome levels. In this release, the annotation data used in the reconstruction of transcripts based on the methodology of ternary matrices were acquired from new databases such as Ensembl, UniProt, and APPRIS. Another innovation implemented in the pipeline is the exclusion of transcripts predicted to be susceptible to degradation through the NMD pathway. Taken together, our repository and its applications represent a valuable resource for the proteogenomics community.

One enzyme, many faces: urease is also canatoxin

Ureases catalyze the hydrolysis of urea into carbamate and ammonia. Well-conserved proteins, most plant ureases are hexamers of a single chain subunit, like the most abundant isoform of the jack bean (Canavalia ensiformis) urease (JBU). Canatoxin (CNTX) was originally isolated from these seeds as a neurotoxic protein, and later characterized as an isoform of JBU with lower molecular mass and enzyme activity. Inactive CNTX oligomers form upon storage and stabilization of CNTX was achieved by treatment with low concentration of formaldehyde, avoiding its oligomerization. Here, nano-LC-MS/MS-based peptide analysis of CNTX revealed 804 amino acids identical to those of JBU's sequence (840 amino acids). De novo sequencing of CNTX revealed 15 different peptides containing substitution of amino acid residues, denoting CNTX as a product of a paralog gene of JBU. The MS/MS analysis of formaldehyde-treated CNTX showed that amino acid residues located at the trimer-trimer interface of JBU's hexamer were modified. The data confirmed that CNTX is an isoform of JBU and elucidated that stabilization by formaldehyde treatment occurs by modification of amino acids at the protein's surface that prevents the formation of the hexamer and of higher molecular mass inactive aggregates. HIGHLIGHTSCanatoxin (CNTX) is an isoform of jack bean urease (JBU, hexamer of 90 kDa chains)MS/MS sequencing of CNTX showed 804 amino acids identical in JBU (840 residues)Formaldehyde treatment of CNTX stabilizes its toxicity and avoids oligomerizationModified amino acid residues in CNTX are at the trimer-trimer interface of JBUCommunicated by Ramaswamy H. Sarma.

4D DIA-PRM proteomic study identifying modulated pathways and biomarkers associated with pelvic organ prolapse

Pelvic organ prolapse (POP) is a highly disabling condition that negatively affects the quality of life of millions of women worldwide. However, the underlying mechanisms associated with the development and progression of the disease remain poorly understood. Here, an untargeted four-dimensional data-independent acquisition (4D DIA)-based proteomics approach was applied to vaginal wall tissue samples from POP (n = 19) and control (n = 8) patients to identify potential diagnostic biomarker(s) for POP and examine the molecular mechanisms underlying the disease. Of the 5713 tissue proteins that were detected, 1957 proteins were significantly changed in POP patients. Further bioinformatics analysis revealed that multiple biological processes including protein digestion & absorption, retrograde endocannabinoid signaling, tyrosine metabolism, and nucleotide metabolism were significantly enriched and associated with the pathogenesis of POP. Interestingly, 16 of these differentially expressed proteins associated with four pathways were also identified by targeted parallel reaction monitoring (PRM) proteomics analysis on the same 27 tissue samples. Changes in 94 % (15/16) of these proteins were consistent with the 4D DIA data. Furthermore, most proteins displayed good diagnostic accuracy with high area under the curve (AUC) values (AUC＞0.8). Specifically, five proteins including ELN, COL6A2, ENTPD1, AOC3, and COX7A2 distinguished between POP and control patients with very high accuracy (AUC ≥ 0.95) in both 4D DIA and PRM analyses, and may therefore be potential diagnostic biomarkers for POP. In summary, the present study not only provided several potential biomarker(s) for effective POP diagnosis, but extended our knowledge of the key regulatory pathways associated with the disease.

Beyond the identifiable proteome: Delving into the proteomics of polymyxin-resistant and non-resistant Acinetobacter baumannii from Brazilian hospitals

This work discloses a unique, comprehensive proteomic dataset of Acinetobacter baumannii strains, both resistant and non-resistant to polymyxin B, isolated in Brazil generated using Orbitrap Fusion Lumos. From nearly 4 million tandem mass spectra, the software DiagnoMass produced 240,685 quality-filtered mass spectral clusters, of which PatternLab for proteomics identified 44,553 peptides mapping to 3479 proteins. Crucially, DiagnoMass shortlisted 3550 and 1408 unique mass spectral clusters for the resistant and non-resistant strains, respectively, with only about a third with sequences (and PTMs) identified by PatternLab. Further open-search attempts via FragPipe yielded an additional ∼20% identifications, suggesting the remaining unidentified spectra likely arise from complex combinations of post-translational modifications and amino-acid substitutions. This highlights the untapped potential of the dataset for future discoveries, particularly given the importance of PTMs, which remain elusive to nucleotide sequencing approaches but are crucial for understanding biological mechanisms. Our innovative approach extends beyond the identifications that are typically subjected to the bias of a search engine; we discern which spectral clusters are differential and subject them to increased scrutiny, akin to spectral library matching by comparing captured spectra to themselves. Our analysis reveals adaptations in the resistant strain, including enhanced detoxification, altered protein synthesis, and metabolic adjustments. SIGNIFICANCE: We present comprehensive proteomic profiles of non-resistant and resistant Acinetobacter baumannii from Brazilian Hospitals strains, and highlight the presence of discriminative and yet unidentified mass spectral clusters. Our work emphasizes the importance of exploring this overlooked data, as it could hold the key to understanding the complex dynamics of antibiotic resistance. This approach not only informs antimicrobial stewardship efforts but also paves the way for the development of innovative diagnostic tools. Thus, our findings have profound implications for the field, as far as methods for providing a new perspective on diagnosing antibiotic resistance as well as classifying proteomes in general.

Eukaryotic-like gephyrin and cognate membrane receptor coordinate corynebacterial cell division and polar elongation

The order Corynebacteriales includes major industrial and pathogenic Actinobacteria such as Corynebacterium glutamicum or Mycobacterium tuberculosis. These bacteria have multi-layered cell walls composed of the mycolyl-arabinogalactan-peptidoglycan complex and a polar growth mode, thus requiring tight coordination between the septal divisome, organized around the tubulin-like protein FtsZ, and the polar elongasome, assembled around the coiled-coil protein Wag31. Here, using C. glutamicum, we report the discovery of two divisome members: a gephyrin-like repurposed molybdotransferase (Glp) and its membrane receptor (GlpR). Our results show how cell cycle progression requires interplay between Glp/GlpR, FtsZ and Wag31, showcasing a crucial crosstalk between the divisome and elongasome machineries that might be targeted for anti-mycobacterial drug discovery. Further, our work reveals that Corynebacteriales have evolved a protein scaffold to control cell division and morphogenesis, similar to the gephyrin/GlyR system that mediates synaptic signalling in higher eukaryotes through network organization of membrane receptors and the microtubule cytoskeleton.

Differential Precipitation of Proteins: A Simple Protein Fractionation Strategy to Gain Biological Insights with Proteomics

Differential precipitation of proteins (DiffPOP) is a simple technique for fractionating complex protein mixtures. Using stepwise addition of acidified methanol, ten distinct subsets of proteins can be selectively precipitated by centrifugation and identified by mass spectrometry-based proteomics. We have previously shown that the ability of a protein to resist precipitation can be altered by drug binding, which enabled us to identify a novel drug-target interaction. Here, we show that the addition of DiffPOP to a standard LC-MS proteomics workflow results in a three-dimensional separation of peptides that increases protein coverage and peptide identifications. Importantly, DiffPOP reveals solubility differences between proteoforms, potentially providing valuable insights that are typically lost in bottom-up proteomics.

Database Creator for Mass Analysis of Peptides and Proteins, DC-MAPP: A Standalone Tool for Simplifying Manual Analysis of Mass Spectral Data to Identify Peptide/Protein Sequences

Proteomic studies typically involve the use of different types of software for annotating experimental tandem mass spectrometric data (MS/MS) and thereby simplifying the process of peptide and protein identification. For such annotations, these softwares calculate the m/z values of the peptide/protein precursor and fragment ions, for which a database of protein sequences must be provided as an input file. The calculated m/z values are stored as another database, which the user usually cannot view. Database Creator for Mass Analysis of Peptides and Proteins (DC-MAPP) is a novel standalone software that can create custom databases for "viewing" the calculated m/z values of precursor and fragment ions, prior to the database search. It contains three modules. Peptide/Protein sequences as per user's choice can be entered as input to the first module for creating a custom database. In the second module, m/z values must be queried-in, which are searched within the custom database to identify protein/peptide sequences. The third module is suited for peptide mass fingerprinting, which can be used to analyze both ESI and MALDI mass spectral data. The feature of "viewing" the custom database can be helpful not only for better understanding the search engine processes, but also for designing multiple reaction monitoring (MRM) methods. Post-translational modifications and protein isoforms can also be analyzed. Since, DC-MAPP relies on the protein/peptide "sequences" for creating custom databases, it may not be applicable for the searches involving spectral libraries. Python language was used for implementation, and the graphical user interface was built with Page/Tcl, making this tool more user-friendly. It is freely available at https://vit.ac.in/DC-MAPP/.

Soluble SARS-CoV-2 RBD and human ACE2 peptidase domain produced in Drosophila S2 cells show functions evoking virus-cell interface

The interaction between the receptor-binding domain (RBD) of the spike glycoprotein of SARS-CoV-2 and the peptidase domain of the human angiotensin-converting enzyme 2 (ACE2) allows the first specific contact at the virus-cell interface making it the main target of neutralizing antibodies. Here, we show a unique and cost-effective protocol using Drosophila S2 cells to produce both RBD and soluble human ACE2 peptidase domain (shACE2) as thermostable proteins, purified via Strep-tag with yields >40 mg L-1 in a laboratory scale. Furthermore, we demonstrate its binding with KD values in the lower nanomolar range (independently of Strep-tag removal) and its capability to be blocked by serum antibodies in a competition ELISA with Strep-Tactin-HRP as a proof-of-concept. In addition, we assess the capacity of RBD to bind native dimeric ACE2 overexpressed in human cells and its antigen properties with specific serum antibodies. Finally, for completeness, we analyzed RBD microheterogeneity associated with glycosylation and negative charges, with negligible effect on binding either with antibodies or shACE2. Our system represents an accessible and reliable tool for designing in-house surrogate virus neutralization tests (sVNTs), enabling the rapid characterization of neutralizing humoral responses elicited against vaccines or infection, especially in the absence of facilities to conduct virus neutralization tests. Moreover, our biophysical and biochemical characterization of RBD and shACE2 produced in S2 cells lays the groundwork for adapting to different variants of concern (VOCs) to study humoral responses elicited against different VOCs and vaccine formulations.

Characteristics of Mycobacterium tuberculosis PtpA interaction and activity on the alpha subunit of human mitochondrial trifunctional protein, a key enzyme of lipid metabolism

During Mycobacterium tuberculosis (Mtb) infection, the virulence factor PtpA belonging to the protein tyrosine phosphatase family is delivered into the cytosol of the macrophage. PtpA interacts with numerous eukaryotic proteins modulating phagosome maturation, innate immune response, apoptosis, and potentially host-lipid metabolism, as previously reported by our group. In vitro, the human trifunctional protein enzyme (hTFP) is a bona fide PtpA substrate, a key enzyme of mitochondrial β-oxidation of long-chain fatty acids, containing two alpha and two beta subunits arranged in a tetramer structure. Interestingly, it has been described that the alpha subunit of hTFP (ECHA, hTFPα) is no longer detected in mitochondria during macrophage infection with the virulent Mtb H37Rv. To better understand if PtpA could be the bacterial factor responsible for this effect, in the present work, we studied in-depth the PtpA activity and interaction with hTFP_α. With this aim, we performed docking and in vitro dephosphorylation assays defining the P-Tyr-271 as the potential target of mycobacterial PtpA, a residue located in the helix-10 of hTFP_α, previously described as relevant for its mitochondrial membrane localization and activity. Phylogenetic analysis showed that Tyr-271 is absent in TFP_α of bacteria and is present in more complex eukaryotic organisms. These results suggest that this residue is a specific PtpA target, and its phosphorylation state is a way of regulating its subcellular localization. We also showed that phosphorylation of Tyr-271 can be catalyzed by Jak kinase. In addition, we found by molecular dynamics that PtpA and hTFP_α form a stable protein complex through the PtpA active site, and we determined the dissociation equilibrium constant. Finally, a detailed study of PtpA interaction with ubiquitin, a reported PtpA activator, showed that additional factors are required to explain a ubiquitin-mediated activation of PtpA. Altogether, our results provide further evidence supporting that PtpA could be the bacterial factor that dephosphorylates hTFP_α during infection, potentially affecting its mitochondrial localization or β-oxidation activity.

DiagnoMass: A proteomics hub for pinpointing discriminative spectral clusters

MOTIVATION

There are several well-established paradigms for identifying and pinpointing discriminative peptides/proteins using shotgun proteomic data; examples are peptide-spectrum matching, de novo sequencing, open searches, and even hybrid approaches. Such an arsenal of complementary paradigms can provide deep data coverage, albeit some unidentified discriminative peptides remain.

RESULTS

We present DiagnoMass, software tool that groups similar spectra into spectral clusters and then shortlists those clusters that are discriminative for biological conditions. DiagnoMass then communicates with proteomic tools to attempt the identification of such clusters. We demonstrate the effectiveness of DiagnoMass by analyzing proteomic data from Escherichia coli, Salmonella, and Shigella, listing many high-quality discriminative spectral clusters that had thus far remained unidentified by widely adopted proteomic tools. DiagnoMass can also classify proteomic profiles. We anticipate the use of DiagnoMass as a vital tool for pinpointing biomarkers.

AVAILABILITY

DiagnoMass and related documentation, including a usage protocol, are available at http://www.diagnomass.com.

PatternLab V Handles Multiplex Spectra in Shotgun Proteomic Searches and Increases Identification

Complex protein mixtures typically generate many tandem mass spectra produced by different peptides coisolated in the gas phase. Widely adopted proteomic data analysis environments usually fail to identify most of these spectra, succeeding at best in identifying only one of the multiple cofragmenting peptides. We present PatternLab V (PLV), an updated version of PatternLab that integrates the YADA 3 deconvolution algorithm to handle such cases efficiently. In general, we expect an increase of 10% in spectral identifications when dealing with complex proteomic samples. PLV is freely available at http://patternlabforproteomics.org.

Genomic–proteomic analysis of a novel Bacillus thuringiensis strain: toxicity against two lepidopteran pests, abundance of Cry1Ac5 toxin, and presence of InhA1 virulence factor

Bacillus thuringiensis (Bt) is a biological alternative to the indiscriminate use of chemical insecticides in agriculture. Due to resistance development on insect pests to Bt crops, isolating novel Bt strains is a strategy for screening new pesticidal proteins or strains containing toxin profile variety that can delay resistance. Besides, the combined genomic and proteomic approaches allow identifying pesticidal proteins and virulence factors accurately. Here, the genome of a novel Bt strain (Bt TOL651) was sequenced, and the proteins from the spore-crystal mixture were identified by proteomic analysis. Toxicity bioassays with the spore-crystal mixture against larvae of Diatraea saccharalis and Anticarsia gemmatalis, key pests of sugarcane and soybean, respectively, were performed. The toxicity of Bt TOL651 varies with the insect; A. gemmatalis (LC₅₀ = 1.45 ng cm^-2) is more susceptible than D. saccharalis (LC₅₀ = 73.77 ng cm^-2). Phylogenetic analysis of the gyrB gene indicates that TOL651 is related to Bt kenyae strains. The genomic analysis revealed the presence of cry1Aa18, cry1Ac5, cry1Ia44, and cry2Aa9 pesticidal genes. Virulence factor genes such as phospholipases (plcA, piplc), metalloproteases (inhA), hemolysins (cytK, hlyIII, hblA, hblC, hblD), and enterotoxins (nheA, nheB, nheC) were also identified. The combined use of the genomic and proteomic data indicated the expression of Cry1Aa18, Cry1Ac5, and Cry2Aa9 proteins, with Cry1Ac5 being the most abundant. InhA1 also was expressed and may contribute to Bt TOL651 pathogenicity. These results provide Bt TOL651 as a new tool for the biocontrol of lepidopteran pests.

Mebendazole Inhibits Histoplasma capsulatum In Vitro Growth and Decreases Mitochondrion and Cytoskeleton Protein Levels

Histoplasmosis is a frequent mycosis in people living with HIV/AIDS and other immunocompromised hosts. Histoplasmosis has high rates of mortality in these patients if treatment is unsuccessful. Itraconazole and amphotericin B are used to treat histoplasmosis; however, both antifungals have potentially severe pharmacokinetic drug interactions and toxicity. The present study determined the minimal inhibitory and fungicidal concentrations of mebendazole, a drug present in the NIH Clinical Collection, to establish whether it has fungicidal or fungistatic activity against Histoplasma capsulatum. Protein extracts from H. capsulatum yeasts, treated or not with mebendazole, were analyzed by proteomics to understand the metabolic changes driven by this benzimidazole. Mebendazole inhibited the growth of 10 H. capsulatum strains, presenting minimal inhibitory concentrations ranging from 5.0 to 0.08 µM. Proteomics revealed 30 and 18 proteins exclusively detected in untreated and mebendazole-treated H. capsulatum yeast cells, respectively. Proteins related to the tricarboxylic acid cycle, cytoskeleton, and ribosomes were highly abundant in untreated cells. Proteins related to the nitrogen, sulfur, and pyrimidine metabolisms were enriched in mebendazole-treated cells. Furthermore, mebendazole was able to inhibit the oxidative metabolism, disrupt the cytoskeleton, and decrease ribosomal proteins in H. capsulatum. These results suggest mebendazole as a drug to be repurposed for histoplasmosis treatment.

Eukaryotic-like gephyrin and cognate membrane receptor coordinate corynebacterial cell division and polar elongation

The order Corynebacteriales includes major industrial and pathogenic actinobacteria such as Corynebacterium glutamicum or Mycobacterium tuberculosis . Their elaborate multi-layered cell wall, composed primarily of the mycolyl-arabinogalactan-peptidoglycan complex, and their polar growth mode impose a stringent coordination between the septal divisome, organized around the tubulin-like protein FtsZ, and the polar elongasome, assembled around the tropomyosin-like protein Wag31. Here, we report the identification of two new divisome members, a gephyrin-like repurposed molybdotransferase (GLP) and its membrane receptor (GLPR). We show that the interplay between the GLPR/GLP module, FtsZ and Wag31 is crucial for orchestrating cell cycle progression. Our results provide a detailed molecular understanding of the crosstalk between two essential machineries, the divisome and elongasome, and reveal that Corynebacteriales have evolved a protein scaffold to control cell division and morphogenesis similar to the gephyrin/GlyR system that in higher eukaryotes mediates synaptic signaling through network organization of membrane receptors and the microtubule cytoskeleton.

Comprehensive proteomic profiling of early antral follicles from sheep

The present study evaluates the proteome of early antral follicles from Ovis aries. Fifty follicles were collected from ovaries of adult ewes and extracted proteins were trypsin-digested, desalted and analyzed by LC-MS/MS. Genes were screened for potential modulation by miRNAs and protein data, subjected to functional enrichment analysis. Label-free mass spectrometry allowed the identification of 2503 follicle proteins, confirming vimentin, actin, lamin, heat shock proteins and histones as the most abundant ones. In silico analyses indicated that miRNAs modulate the expression of genes coding proteins of the sheep follicles involved in cell cycle, cell differentiation, aging, apoptosis, cell death, adipocyte differentiation, cell division. The most important biological processes associated with the follicle proteins were innate immune response, translation, adaptive immune response and protein folding, while molecular functions linked to the proteome of sheep antral follicles related to metal ion binding, ATP binding, oxygen binding, RNA binding and GTP binding, among others. Upload of 2503 Uniport accession codes through DAVID platform matched 1274 genes, associated with translation, metabolic process, proteolysis involved in cellular protein catabolic process, zona pellucida receptor complex and others. KEEG pathways analysis indicated genes correlated with ovine follicular development, with major pathways listed as carbon metabolism, biosynthesis of amino acids, glutathione metabolism, oxidative phosphorylation, fatty acid degradation and oocyte meiosis. This represents a comprehensive atlas of proteins expressed in sheep early antral follicles and will contribute to future identification of biomarkers for follicular development and oocyte maturation.

Increasing confidence in proteomic spectral deconvolution through mass defect

MOTIVATION

Confident deconvolution of proteomic spectra is critical for several applications such as de novo sequencing, cross-linking mass spectrometry and handling chimeric mass spectra.

RESULTS

In general, all deconvolution algorithms may eventually report mass peaks that are not compatible with the chemical formula of any peptide. We show how to remove these artifacts by considering their mass defects. We introduce Y.A.D.A. 3.0, a fast deconvolution algorithm that can remove peaks with unacceptable mass defects. Our approach is effective for polypeptides with less than 10 kDa, and its essence can be easily incorporated into any deconvolution algorithm.

AVAILABILITY AND IMPLEMENTATION

Y.A.D.A. 3.0 is freely available for academic use at http://patternlabforproteomics.org/yada3.

SUPPLEMENTARY INFORMATION

Supplementary information is available at Bioinformatics online.

Identification of Novel Genes and Proteoforms in Angiostrongylus costaricensis through a Proteogenomic Approach

RNA sequencing (RNA-Seq) and mass-spectrometry-based proteomics data are often integrated in proteogenomic studies to assist in the prediction of eukaryote genome features, such as genes, splicing, single-nucleotide (SNVs), and single-amino-acid variants (SAAVs). Most genomes of parasite nematodes are draft versions that lack transcript- and protein-level information and whose gene annotations rely only on computational predictions. Angiostrongylus costaricensis is a roundworm species that causes an intestinal inflammatory disease, known as abdominal angiostrongyliasis (AA). Currently, there is no drug available that acts directly on this parasite, mostly due to the sparse understanding of its molecular characteristics. The available genome of A. costaricensis, specific to the Costa Rica strain, is a draft version that is not supported by transcript- or protein-level evidence. This study used RNA-Seq and MS/MS data to perform an in-depth annotation of the A. costaricensis genome. Our prediction improved the reference annotation with (a) novel coding and non-coding genes; (b) pieces of evidence of alternative splicing generating new proteoforms; and (c) a list of SNVs between the Brazilian (Crissiumal) and the Costa Rica strain. To the best of our knowledge, this is the first time that a multi-omics approach has been used to improve the genome annotation of A. costaricensis. We hope this improved genome annotation can assist in the future development of drugs, kits, and vaccines to treat, diagnose, and prevent AA caused by either the Brazil strain (Crissiumal) or the Costa Rica strain.

Non-target molecular network and putative genes of flavonoid biosynthesis in Erythrina velutina Willd., a Brazilian semiarid native woody plant

Erythrina velutina is a Brazilian native tree of the Caatinga (a unique semiarid biome). It is widely used in traditional medicine showing anti-inflammatory and central nervous system modulating activities. The species is a rich source of specialized metabolites, mostly alkaloids and flavonoids. To date, genomic information, biosynthesis, and regulation of flavonoids remain unknown in this woody plant. As part of a larger ongoing research goal to better understand specialized metabolism in plants inhabiting the harsh conditions of the Caatinga, the present study focused on this important class of bioactive phenolics. Leaves and seeds of plants growing in their natural habitat had their metabolic and proteomic profiles analyzed and integrated with transcriptome data. As a result, 96 metabolites (including 43 flavonoids) were annotated. Transcripts of the flavonoid pathway totaled 27, of which EvCHI, EvCHR, EvCHS, EvCYP75A and EvCYP75B1 were identified as putative main targets for modulating the accumulation of these metabolites. The highest correspondence of mRNA vs. protein was observed in the differentially expressed transcripts. In addition, 394 candidate transcripts encoding for transcription factors distributed among the bHLH, ERF, and MYB families were annotated. Based on interaction network analyses, several putative genes of the flavonoid pathway and transcription factors were related, particularly TFs of the MYB family. Expression patterns of transcripts involved in flavonoid biosynthesis and those involved in responses to biotic and abiotic stresses were discussed in detail. Overall, these findings provide a base for the understanding of molecular and metabolic responses in this medicinally important species. Moreover, the identification of key regulatory targets for future studies aiming at bioactive metabolite production will be facilitated.

Combination of E- and NS1-Derived DNA Vaccines: The Immune Response and Protection Elicited in Mice against DENV2

The occurrence of dengue disease has increased radically in recent decades. Previously, we constructed the pE1D2 and pcTPANS1 DNA vaccines encoding the DENV2 envelope (E) and non-structural 1 (NS1) proteins, respectively. To decrease the number of plasmids in a tetravalent candidate vaccine, we constructed a bicistronic plasmid, pNS1/E/D2, encoding these two proteins simultaneously. We evaluated the protective immunity induced in mice vaccinated with the pNS1/E/D2 candidate and compared to the responses elicited by immunization with the former vaccines isolated or in combination. We transfected BHK-21 cells with the different plasmids and detected recombinant proteins by immunofluorescence and mass spectrometry assays to confirm antigen expression. BALB/c mice were inoculated with the DNA vaccines followed by a lethal DENV2 challenge. ELISA, PRNT50, and IFN-gamma ELISPOT assays were performed for the investigation of the humoral and cellular responses. We observed the concomitant expression of NS1 and E proteins in pNS1/E/D2-transfected cells. All E-based vaccines induced anti-E and neutralizing antibodies. However, anti-NS1 antibodies were only observed after immunization with the pcTPANS1 administered alone or combined with pE1D2. In contrast, splenocytes from pNS1/E/D2- or pcTPANS1 + pE1D2-vaccinated animals responded to NS1- and E-derived synthetic peptides. All the DNA vaccines conferred protection against DENV2.

Insights from a Multi-Omics Integration (MOI) Study in Oil Palm (Elaeis guineensis Jacq.) Response to Abiotic Stresses: Part One—Salinity

Oil palm (Elaeis guineensis Jacq.) is the number one source of consumed vegetable oil nowadays. It is cultivated in areas of tropical rainforest, where it meets its natural condition of high rainfall throughout the year. The palm oil industry faces criticism due to a series of practices that was considered not environmentally sustainable, and it finds itself under pressure to adopt new and innovative procedures to reverse this negative public perception. Cultivating this oilseed crop outside the rainforest zone is only possible using artificial irrigation. Close to 30% of the world’s irrigated agricultural lands also face problems due to salinity stress. Consequently, the research community must consider drought and salinity together when studying to empower breeding programs in order to develop superior genotypes adapted to those potential new areas for oil palm cultivation. Multi-Omics Integration (MOI) offers a new window of opportunity for the non-trivial challenge of unraveling the mechanisms behind multigenic traits, such as drought and salinity tolerance. The current study carried out a comprehensive, large-scale, single-omics analysis (SOA), and MOI study on the leaves of young oil palm plants submitted to very high salinity stress. Taken together, a total of 1239 proteins were positively regulated, and 1660 were negatively regulated in transcriptomics and proteomics analyses. Meanwhile, the metabolomics analysis revealed 37 metabolites that were upregulated and 92 that were downregulated. After performing SOA, 436 differentially expressed (DE) full-length transcripts, 74 DE proteins, and 19 DE metabolites underwent MOI analysis, revealing several pathways affected by this stress, with at least one DE molecule in all three omics platforms used. The Cysteine and methionine metabolism (map00270) and Glycolysis/Gluconeogenesis (map00010) pathways were the most affected ones, each one with 20 DE molecules.