The development of a novel zeolite-based assay for efficient and deep plasma proteomic profiling.

Plasma proteins are considered the most informative source of biomarkers for disease diagnosis and monitoring. Mass spectrometry (MS)-based proteomics has been applied to identify biomarkers in plasma, but the complexity of the plasma proteome and the extremely large dynamic range of protein abundances in plasma make the clinical application of plasma proteomics highly challenging. We designed and synthesized zeolite-based nanoparticles to deplete high-abundance plasma proteins. The resulting novel plasma proteomic assay can measure approximately 3000 plasma proteins in a 45 min chromatographic gradient. Compared to those in neat and depleted plasma, the plasma proteins identified by our assay exhibited distinct biological profiles, as validated in several public datasets. A pilot investigation of the proteomic profile of a hepatocellular carcinoma (HCC) cohort identified 15 promising protein features, highlighting the diagnostic value of the plasma proteome in distinguishing individuals with and without HCC. Furthermore, this assay can be easily integrated with all current downstream protein profiling methods and potentially extended to other biofluids. In conclusion, we established a robust and efficient plasma proteomic assay with unprecedented identification depth, paving the way for the translation of plasma proteomics into clinical applications.

Sample Preparation and Phosphopeptide Enrichment for Plant Phosphoproteomics via Label-Free Mass Spectrometry.

Phosphopeptide enrichment is the main bottleneck of every phosphorylation study. Therefore, in this chapter, a general workflow tries to overbridge the hurdles of plant sample handling from sample collection to protein extraction, protein solubilization, enzymatic digestion, and enrichment step prior to mass spectrometry. The workflow provides information to perform global proteomics as well as phosphoproteomics enabling the researcher to use the protocol in both fields.

Optimizing environmental enrichment for Sprague Dawley rats: Exemplary insights into the liver proteome.

BACKGROUND: Considering the expected increase in the elderly population and the growing emphasis on aging-related biomedical research, the demand for aged laboratory animals has surged, challenging established husbandry practices. Our objective was to establish a cost-effective method for environmental enrichment, utilizing the liver as a representative organ to assess potential metabolic changes in response to differing enrichment levels. METHODS: We conducted a six-month study involving 24 male Sprague Dawley rats, randomly assigned to four environmental enrichment groups. Two groups were housed in standard cages, while the others were placed in modified rabbit cages. Half of the groups received weekly playtime in an activity focused rat housing unit. We evaluated hormone levels, playtime behavior, and subjective handling experience. Additionally, liver tissue proteomic analysis was performed. RESULTS: Initial corticosterone levels and those after 3 and 6 months showed no significant differences. Yet, testosterone levels were lower in the control group by the end of the study (p = 0.007). We observed 1871 distinct proteins in liver tissue, with 77% being common across groups. In gene ontology analysis, no specific pathways were overexpressed. In semiquantitative analysis, we observed differences in proteins associated in lipid metabolism such as Apolipoprotein A-I and Acyl-CoA 6-desaturase, which were lower in the control group (p = 0.024 and p = 0.009). Rats in the intervention groups with weekly playtime displayed the least amount of reported distress during inspection or upon room entry and were less prone to accepting treats. Removing animals from their enclosure was most effortless for those in the large cage group. Over time, there was a decrease in conflicts among rats that interacted only twice weekly during playpen time. DISCUSSION: In summary, refining husbandry practices for aging rats is both simple and budget-friendly, with no apparent adverse effects on stress levels, animal development, or relevant metabolic changes in the liver.

The effects of immortalization on the N-glycome and proteome of CDK4-transformed lung cancer cells.

Biological experiments are often conducted in vitro using immortalized cells due to their accessibility and ease of propagation compared to primary cells and live animals. However, immortalized cells may present different proteomic and glycoproteomic characteristics from the primary cell source due to the introduction of genes that enhance proliferation (e.g. CDK4) or enable telomere lengthening. To demonstrate the changes in phenotype upon CDK4-transformation, we performed LC-MS/MS glycomic and proteomic characterizations of a human lung cancer primary cell line (DTW75) and a CDK4-transformed cell line (GL01) derived from DTW75. We observed that the primary and CDK4-transformed cells expressed significantly different levels of sialylated, fucosylated, and sialofucosylated N-glycans. Specifically, the primary cells expressed higher levels of hybrid- and complex-type sialylated N-glycans, while CDK4-transformed cells expressed higher levels of complex-type fucosylated and sialofucosylated N-glycans. Further, we compared the proteomic differences between the cell lines and found that CDK4-transformed cells expressed higher levels of RNA-binding and adhesion proteins. Further, we observed that the CDK4-transformed cells changed N-glycosylation after 31 days in cell culture, with a decrease in high-mannose and increase in fucosylated, sialylated, and sialofucosylated N-glycans. Identifying these changes between primary and CDK4-transformed cells will provide useful insight when adapting cell lines that more closely resemble in vivo physiological conditions.

Impact of inflammatory preconditioning on murine microglial proteome response induced by focal ischemic brain injury.

Preconditioning with lipopolysaccharide (LPS) induces neuroprotection against subsequent cerebral ischemic injury, mainly involving innate immune pathways. Microglia are resident immune cells of the central nervous system (CNS) that respond early to danger signals through memory-like differential reprogramming. However, the cell-specific molecular mechanisms underlying preconditioning are not fully understood. To elucidate the distinct molecular mechanisms of preconditioning on microglia, we compared these cell-specific proteomic profiles in response to LPS preconditioning and without preconditioning and subsequent transient focal brain ischemia and reperfusion, - using an established mouse model of transient focal brain ischemia and reperfusion. A proteomic workflow, based on isolated microglia obtained from mouse brains by cell sorting and coupled to mass spectrometry for identification and quantification, was applied. Our data confirm that LPS preconditioning induces marked neuroprotection, as indicated by a significant reduction in brain infarct volume. The established brain cell separation method was suitable for obtaining an enriched microglial cell fraction for valid proteomic analysis. The results show a significant impact of LPS preconditioning on microglial proteome patterns by type I interferons, presumably driven by the interferon cluster regulator proteins signal transducer and activator of transcription1/2 (STAT1/2).

Multimodal joint deconvolution and integrative signature selection in proteomics.

Deconvolution is an efficient approach for detecting cell-type-specific (cs) transcriptomic signals without cellular segmentation. However, this type of methods may require a reference profile from the same molecular source and tissue type. Here, we present a method to dissect bulk proteome by leveraging tissue-matched transcriptome and proteome without using a proteomics reference panel. Our method also selects the proteins contributing to the cellular heterogeneity shared between bulk transcriptome and proteome. The deconvoluted result enables downstream analyses such as cs-protein Quantitative Trait Loci (cspQTL) mapping. We benchmarked the performance of this multimodal deconvolution approach through CITE-seq pseudo bulk data, a simulation study, and the bulk multi-omics data from human brain normal tissues and breast cancer tumors, individually, showing robust and accurate cell abundance quantification across different datasets. This algorithm is implemented in a tool MICSQTL that also provides cspQTL and multi-omics integrative visualization, available at https://bioconductor.org/packages/MICSQTL .

Unveiling Cryptosporidium parvum sporozoite-derived extracellular vesicles: profiling, origin, and protein composition.

Cryptosporidium parvum is a common cause of a zoonotic disease and a main cause of diarrhea in newborns. Effective drugs or vaccines are still lacking. Oocyst is the infective form of the parasite; after its ingestion, the oocyst excysts and releases four sporozoites into the host intestine that rapidly attack the enterocytes. The membrane protein CpRom1 is a large rhomboid protease that is expressed by sporozoites and recognized as antigen by the host immune system. In this study, we observed the release of CpRom1 with extracellular vesicles (EVs) that was not previously described. To investigate this phenomenon, we isolated and resolved EVs from the excystation medium by differential ultracentrifugation. Fluorescence flow cytometry and transmission electron microscopy (TEM) experiments identified two types of sporozoite-derived vesicles: large extracellular vesicles (LEVs) and small extracellular vesicles (SEVs). Nanoparticle tracking analysis (NTA) revealed mode diameter of 181 nm for LEVs and 105 nm for SEVs, respectively. Immunodetection experiments proved the presence of CpRom1 and the Golgi protein CpGRASP in LEVs, while immune-electron microscopy trials demonstrated the localization of CpRom1 on the LEVs surface. TEM and scanning electron microscopy (SEM) showed that LEVs were generated by means of the budding of the outer membrane of sporozoites; conversely, the origin of SEVs remained uncertain. Distinct protein compositions were observed between LEVs and SEVs as evidenced by their corresponding electrophoretic profiles. Indeed, a dedicated proteomic analysis identified 5 and 16 proteins unique for LEVs and SEVs, respectively. Overall, 60 proteins were identified in the proteome of both types of vesicles and most of these proteins (48 in number) were already identified in the molecular cargo of extracellular vesicles from other organisms. Noteworthy, we identified 12 proteins unique to Cryptosporidium spp. and this last group included the immunodominant parasite antigen glycoprotein GP60, which is one of the most abundant proteins in both LEVs and SEVs.

Metabolomics and proteomics insights into subacute ruminal acidosis etiology and inhibition of proliferation of yak rumen epithelial cells in vitro.

BACKGROUND: Untargeted metabolomics and proteomics were employed to investigate the intracellular response of yak rumen epithelial cells (YRECs) to conditions mimicking subacute rumen acidosis (SARA) etiology, including exposure to short-chain fatty acids (SCFA), low pH5.5 (Acid), and lipopolysaccharide (LPS) exposure for 24 h. RESULTS: These treatments significantly altered the cellular morphology of YRECs. Metabolomic analysis identified significant perturbations with SCFA, Acid and LPS treatment affecting 259, 245 and 196 metabolites (VIP > 1, P < 0.05, and fold change (FC) ≥ 1.5 or FC ≤ 0.667). Proteomic analysis revealed that treatment with SCFA, Acid, and LPS resulted in differential expression of 1251, 1396, and 242 proteins, respectively (FC ≥ 1.2 or ≤ 0.83, P < 0.05, FDR < 1%). Treatment with SCFA induced elevated levels of metabolites involved in purine metabolism, glutathione metabolism, and arginine biosynthesis, and dysregulated proteins associated with actin cytoskeleton organization and ribosome pathways. Furthermore, SCFA reduced the number, morphology, and functionality of mitochondria, leading to oxidative damage and inhibition of cell survival. Gene expression analysis revealed a decrease the genes expression of the cytoskeleton and cell cycle, while the genes expression associated with inflammation and autophagy increased (P < 0.05). Acid exposure altered metabolites related to purine metabolism, and affected proteins associated with complement and coagulation cascades and RNA degradation. Acid also leads to mitochondrial dysfunction, alterations in mitochondrial integrity, and reduced ATP generation. It also causes actin filaments to change from filamentous to punctate, affecting cellular cytoskeletal function, and increases inflammation-related molecules, indicating the promotion of inflammatory responses and cellular damage (P < 0.05). LPS treatment induced differential expression of proteins involved in the TNF signaling pathway and cytokine-cytokine receptor interaction, accompanied by alterations in metabolites associated with arachidonic acid metabolism and MAPK signaling (P < 0.05). The inflammatory response and activation of signaling pathways induced by LPS treatment were also confirmed through protein interaction network analysis. The integrated analysis reveals co-enrichment of proteins and metabolites in cellular signaling and metabolic pathways. CONCLUSIONS: In summary, this study contributes to a comprehensive understanding of the detrimental effects of SARA-associated factors on YRECs, elucidating their molecular mechanisms and providing potential therapeutic targets for mitigating SARA.

Proteomic studies in VWA1-related neuromyopathy allowed new pathophysiological insights and the definition of blood biomarkers.

Bi-allelic variants in VWA1, encoding Von Willebrand Factor A domain containing 1 protein localized to the extracellular matrix (ECM), were linked to a neuromuscular disorder with manifestation in child- or adulthood. Clinical findings indicate a neuromyopathy presenting with muscle weakness. Given that pathophysiological processes are still incompletely understood, and biomarkers are still missing, we aimed to identify blood biomarkers of pathophysiological relevance: white blood cells (WBC) and plasma derived from six VWA1-patients were investigated by proteomics. Four proteins, BET1, HNRNPDL, NEFM and PHGDH, known to be involved in neurological diseases and dysregulated in WBC were further validated by muscle-immunostainings unravelling HNRNPDL as a protein showing differences between VWA1-patients, healthy controls and patients suffering from neurogenic muscular atrophy and BICD2-related neuromyopathy. Immunostaining studies of PHGDH indicate its involvement in apoptotic processes via co-localisation with caspase-3. NEFM showed an increase in cells within the ECM in biopsies of all patients studied. Plasma proteomics unravelled dysregulation of 15 proteins serving as biomarker candidates among which a profound proportion of increased ones (6/11) are mostly related to antioxidative processes and have even partially been described as blood biomarkers for other entities of neuromuscular disorders before. CRP elevated in plasma also showed an increase in the extracellular space of VWA1-mutant muscle. Results of our combined studies for the first time describe pathophysiologically relevant biomarkers for VWA1-related neuromyopathy and suggest that VWA1-patient derived blood might hold the potential to study disease processes of clinical relevance, an important aspect for further preclinical studies.

The effect of feeding on different hosts on the egg proteins in Haemaphysalis qinghaiensis tick.

The majority of ixodid ticks display host-specificity to varying extents. Feeding on different hosts affects their development and reproduction. Consequences can be analyzed at the level of the egg, as it is the initial stage of tick development. Tick egg proteins are abundant and diverse, providing nutrients for embryonic development. However, studies on tick egg profiles are scarce. In this study, we aimed to analyze whether feeding Haemaphysalis qinghaiensis ticks on the yaks (Bos grunniens) and domestic sheep (Ovis aries) has an impact on the variety and variability of the egg proteome. Detached engorged females were used to lay eggs, which were then collected, dewaxed, and subjected to protein extraction. The extracted egg proteins were enzymatically digested using Filter-Aided Sample Preparation (FASP), and the unique peptides were separated and detected by Liquid Chromatography-tandem Mass Spectrometry (LC-MS/MS). The MS data were searched against the previously constructed whole tick transcriptome library of H. qinghaiensis, and the UniProt database for the identification of tick-derived egg proteins. The analysis revealed 49 and 53 high-confidence proteins identified in eggs collected from B. grunniens (EggBg) and O. aries (EggOa), respectively. Of these, 46 high-confidence proteins were common to both egg types, while three were unique to EggBg and seven to EggOa. All the identified proteins mainly belonged to enzymes, enzyme inhibitors, transporters, and proteins with unknown functions. The differential abundance analysis showed that nine proteins were significantly more present in EggBg, while six were significantly more present in EggOa. Overall, enzymes were the most diverse group, while vitellogenin (Vg) was the most abundant. Blood meal uptake on different hosts has a certain effect on the egg proteome composition and the abundance of some proteins, but it may also lead to compensation of protein roles.

Characterization of the Mitochondrial Proteome in the Ctenophore Mnemiopsis leidyi Using MitoPredictor.

Mitochondrial proteomes have been experimentally characterized for only a handful of animal species. However, the increasing availability of genomic and transcriptomic data allows one to infer mitochondrial proteins using computational tools. MitoPredictor is a novel random forest classifier, which utilizes orthology search, mitochondrial targeting signal (MTS) identification, and protein domain content to infer mitochondrial proteins in animals. MitoPredictor's output also includes an easy-to-use R Shiny applet for the visualization and analysis of the results. In this article, we provide a guide for predicting and analyzing the mitochondrial proteome of the ctenophore Mnemiopsis leidyi using MitoPredictor.

Overcoming the detrimental O-acylation in TMTpro labeling improves the proteome depth and quantification precision.

BACKGROUND: With the advent of proline-based reporter isobaric Tandem Mass Tag (TMTpro) reagents, the sample multiplexing capacity of tandem mass tags (TMTs) has been expanded, and up to 18 samples can be quantified in a multiplexed manner. Like classic TMT reagents, TMTpro reagents contain a tertiary amine group, which markedly enhances their reactivity toward hydroxyl groups and results in O-acylation of serine, threonine and tyrosine residues. This overlabeling significantly compromises proteome analysis in terms of depth and precision. In particular, the reactivity of hydroxyl-containing residues can be dramatically enhanced when coexisting with a histidine in the same peptides, leading to a severe systematic bias against the analysis of these peptides. Although some protocols using a reduced molar excess of TMT under alkaline conditions can alleviate overlabeling of histidine-free peptides to some extent, they have a limited effect on histidyl- and hydroxyl-containing peptides. RESULTS: Here, we report a novel TMTpro labeling method that overcomes detrimental overlabeling while providing high labeling efficiency of amines. Additionally, our method is cost-effective, as it requires only half the amount of TMTpro reagents recommended by the reagent manufacturer. In a deep-scale analysis of a yeast/human two-proteome model sample, we compared our method with a typical alkaline labeling method using a reduced molar excess of TMTpro. Even at a depth of over 10,000 proteins, our method detected 23.7% more unique peptides and 8.7% more protein groups compared to the alkaline labeling method. Moreover, our method significantly improved the quantitative precision due to the reduced variability in labeling and increased protein sequence coverage. This substantially enhanced the statistical power of our method for detecting differentially abundant proteins, providing an average of 13% more yeast proteins that reached statistical significance. SIGNIFCANCE: We presented a novel TMTpro labeling method that overcomes the detrimental O-acylation and thus significantly improves the depth and quantitative precision for proteome analysis.

Bacterial proteome adaptation during fermentation in dairy environments.

The enzymatic repertoire of starter cultures belonging to the Lactococcus genus determines various important characteristics of fermented dairy products but might change in response to the substantial environmental changes in the manufacturing process. Assessing bacterial proteome adaptation in dairy and other food environments is challenging due to the high matrix-protein concentration and is even further complicated in particularly cheese by the high fat concentrations, the semi-solid state of that matrix, and the non-growing state of the bacteria. Here, we present bacterial harvesting and processing procedures that enable reproducible, high-resolution proteome determination in lactococcal cultures harvested from laboratory media, milk, and miniature Gouda cheese. Comparative proteome analysis of Lactococcus cremoris NCDO712 grown in laboratory medium and milk revealed proteome adaptations that predominantly reflect the differential (micro-)nutrient availability in these two environments. Additionally, the drastic environmental changes during cheese manufacturing only elicited subtle changes in the L. cremoris NCDO712 proteome, including modified expression levels of enzymes involved in flavour formation. The technical advances we describe offer novel opportunities to evaluate bacterial proteomes in relation to their performance in complex, protein- and/or fat-rich food matrices and highlight the potential of steering starter culture performance by preculture condition adjustments.

Untargeted metabolomics and molecular docking studies on green silver nanoparticles synthesized by Sarocladium subulatum: Exploring antibacterial and antioxidant properties.

The biological synthesis of silver nanoparticles (Ag-NPs) with fungi has shown promising results in antibacterial and antioxidant properties. Fungi generate metabolites (both primary and secondary) and proteins, which aid in the formation of metal nanoparticles as reducing or capping agents. While several studies have been conducted on the biological production of Ag-NPs, the exact mechanisms still need to be clarified. In this study, Ag-NPs are synthesized greenly using an unstudied fungal strain, Sarocladium subulatum AS4D. Three silver salts were used to synthesize the Ag-NPs for the first time, optimized using a cell-free extract (CFE) strategy. Additionally, these NPs were assessed for their antimicrobial and antioxidant properties. Various spectroscopic and microscopy techniques were utilized to confirm Ag-NP formation and analyze their morphology, crystalline properties, functional groups, size, stability, and concentrations. Untargeted metabolomics and proteome disruption were employed to explore the synthesis mechanism. Computational tools were applied to predict metabolite toxicity and antibacterial activity. The study identified 40 fungal metabolites capable of reducing silver ions, with COOH and OH functional groups playing a pivotal role. The silver salt type impacted the NPs' size and stability, with sizes ranging from 40 to 52 nm and zeta potentials from -0.9 to -30.4 mV. Proteome disruption affected size and stability but not shape. Biosynthesized Ag-NPs using protein-free extracts ranged from 55 to 62 nm, and zeta potentials varied from -18 to -27 mV. Molecular docking studies and PASS results found no role for the metabolome in antibacterial activity. This suggests the antibacterial activity comes from Ag-NPs, not capping or reducing agents. Overall, the research affirmed the vital role of specific reducing metabolites in the biosynthesis of Ag-NPs, while proteins derived from biological extracts were found to solely affect their size and stability.

ProNet DB: a proteome-wise database for protein surface property representations and RNA-binding profiles.

The rapid growth in the number of experimental and predicted protein structures and more complicated protein structures poses a significant challenge for computational biology in leveraging structural information and accurate representation of protein surface properties. Recently, AlphaFold2 released the comprehensive proteomes of various species, and protein surface property representation plays a crucial role in protein-molecule interaction predictions, including those involving proteins, nucleic acids and compounds. Here, we proposed the first extensive database, namely ProNet DB, that integrates multiple protein surface representations and RNA-binding landscape for 326 175 protein structures. This collection encompasses the 16 model organism proteomes from the AlphaFold Protein Structure Database and experimentally validated structures from the Protein Data Bank. For each protein, ProNet DB provides access to the original protein structures along with the detailed surface property representations encompassing hydrophobicity, charge distribution and hydrogen bonding potential as well as interactive features such as the interacting face and RNA-binding sites and preferences. To facilitate an intuitive interpretation of these properties and the RNA-binding landscape, ProNet DB incorporates visualization tools like Mol* and an Online 3D Viewer, allowing for the direct observation and analysis of these representations on protein surfaces. The availability of pre-computed features enables instantaneous access for users, significantly advancing computational biology research in areas such as molecular mechanism elucidation, geometry-based drug discovery and the development of novel therapeutic approaches. Database URL:  https://proj.cse.cuhk.edu.hk/aihlab/pronet/.

IMPRINTS.CETSA and IMPRINTS.CETSA.app: an R package and a Shiny application for the analysis and interpretation of IMPRINTS-CETSA data.

IMPRINTS-CETSA (Integrated Modulation of Protein Interaction States-Cellular Thermal Shift Assay) provides a highly resolved means to systematically study the interactions of proteins with other cellular components, including metabolites, nucleic acids and other proteins, at the proteome level, but no freely available and user-friendly data analysis software has been reported. Here, we report IMPRINTS.CETSA, an R package that provides the basic data processing framework for robust analysis of the IMPRINTS-CETSA data format, from preprocessing and normalization to visualization. We also report an accompanying R package, IMPRINTS.CETSA.app, which offers a user-friendly Shiny interface for analysis and interpretation of IMPRINTS-CETSA results, with seamless features such as functional enrichment and mapping to other databases at a single site. For the hit generation part, the diverse behaviors of protein modulations have been typically segregated with a two-measure scoring method, i.e. the abundance and thermal stability changes. We present a new algorithm to classify modulated proteins in IMPRINTS-CETSA experiments by a robust single-measure scoring. In this way, both the numerical changes and the statistical significances of the IMPRINTS information can be visualized on a single plot. The IMPRINTS.CETSA and IMPRINTS.CETSA.app R packages are freely available on GitHub at https://github.com/nkdailingyun/IMPRINTS.CETSA and https://github.com/mgerault/IMPRINTS.CETSA.app, respectively. IMPRINTS.CETSA.app is also available as an executable program at https://zenodo.org/records/10636134.

The long-chain flavodoxin FldX1 improves the biodegradation of 4-hydroxyphenylacetate and 3-hydroxyphenylacetate and counteracts the oxidative stress associated to aromatic catabolism in Paraburkholderia xenovorans.

BACKGROUND: Bacterial aromatic degradation may cause oxidative stress. The long-chain flavodoxin FldX1 of Paraburkholderia xenovorans LB400 counteracts reactive oxygen species (ROS). The aim of this study was to evaluate the protective role of FldX1 in P. xenovorans LB400 during the degradation of 4-hydroxyphenylacetate (4-HPA) and 3-hydroxyphenylacetate (3-HPA). METHODS: The functionality of FldX1 was evaluated in P. xenovorans p2-fldX1 that overexpresses FldX1. The effects of FldX1 on P. xenovorans were studied measuring growth on hydroxyphenylacetates, degradation of 4-HPA and 3-HPA, and ROS formation. The effects of hydroxyphenylacetates (HPAs) on the proteome (LC-MS/MS) and gene expression (qRT-PCR) were quantified. Bioaugmentation with strain p2-fldX1 of 4-HPA-polluted soil was assessed, measuring aromatic degradation (HPLC), 4-HPA-degrading bacteria, and plasmid stability. RESULTS: The exposure of P. xenovorans to 4-HPA increased the formation of ROS compared to 3-HPA or glucose. P. xenovorans p2-fldX1 showed an increased growth on 4-HPA and 3-HPA compared to the control strain WT-p2. Strain p2-fldX1 degraded faster 4-HPA and 3-HPA than strain WT-p2. Both WT-p2 and p2-fldX1 cells grown on 4-HPA displayed more changes in the proteome than cells grown on 3-HPA in comparison to glucose-grown cells. Several enzymes involved in ROS detoxification, including AhpC2, AhpF, AhpD3, KatA, Bcp, CpoF1, Prx1 and Prx2, were upregulated by hydroxyphenylacetates. Downregulation of organic hydroperoxide resistance (Ohr) and DpsA proteins was observed. A downregulation of the genes encoding scavenging enzymes (katE and sodB), and gstA and trxB was observed in p2-fldX1 cells, suggesting that FldX1 prevents the antioxidant response. More than 20 membrane proteins, including porins and transporters, showed changes in expression during the growth of both strains on hydroxyphenylacetates. An increased 4-HPA degradation by recombinant strain p2-fldX1 in soil microcosms was observed. In soil, the strain overexpressing the flavodoxin FldX1 showed a lower plasmid loss, compared to WT-p2 strain, suggesting that FldX1 contributes to bacterial fitness. Overall, these results suggest that recombinant strain p2-fldX1 is an attractive bacterium for its application in bioremediation processes of aromatic compounds. CONCLUSIONS: The long-chain flavodoxin FldX1 improved the capability of P. xenovorans to degrade 4-HPA in liquid culture and soil microcosms by protecting cells against the degradation-associated oxidative stress.

Genetic determinants of plasma protein levels in the Estonian population.

The proteome holds great potential as an intermediate layer between the genome and phenome. Previous protein quantitative trait locus studies have focused mainly on describing the effects of common genetic variations on the proteome. Here, we assessed the impact of the common and rare genetic variations as well as the copy number variants (CNVs) on 326 plasma proteins measured in up to 500 individuals. We identified 184 cis and 94 trans signals for 157 protein traits, which were further fine-mapped to credible sets for 101 cis and 87 trans signals for 151 proteins. Rare genetic variation contributed to the levels of 7 proteins, with 5 cis and 14 trans associations. CNVs were associated with the levels of 11 proteins (7 cis and 5 trans), examples including a 3q12.1 deletion acting as a hub for multiple trans associations; and a CNV overlapping NAIP, a sensor component of the NAIP-NLRC4 inflammasome which is affecting pro-inflammatory cytokine interleukin 18 levels. In summary, this work presents a comprehensive resource of genetic variation affecting the plasma protein levels and provides the interpretation of identified effects.

Adaptive laboratory evolution of Clostridium autoethanogenum to metabolize CO2 and H2 enhances growth rates in chemostat and unravels proteome and metabolome alterations.

Gas fermentation of CO2 and H2 is an attractive means to sustainably produce fuels and chemicals. Clostridium autoethanogenum is a model organism for industrial CO to ethanol and presents an opportunity for CO2-to-ethanol processes. As we have previously characterized its CO2/H2 chemostat growth, here we use adaptive laboratory evolution (ALE) with the aim of improving growth with CO2/H2. Seven ALE lineages were generated, all with improved specific growth rates. ALE conducted in the presence of 2% CO along with CO2/H2 generated Evolved lineage D, which showed the highest ethanol titres amongst all the ALE lineages during the fermentation of CO2/H2. Chemostat comparison against the parental strain shows no change in acetate or ethanol production, while Evolved D could achieve a higher maximum dilution rate. Multi-omics analyses at steady state revealed that Evolved D has widespread proteome and intracellular metabolome changes. However, the uptake and production rates and titres remain unaltered until investigating their maximum dilution rate. Yet, we provide numerous insights into CO2/H2 metabolism via these multi-omics data and link these results to mutations, suggesting novel targets for metabolic engineering in this bacterium.

Systematic proteome-wide Mendelian randomization using the human plasma proteome to identify therapeutic targets for lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is the predominant histological subtype of lung cancer and the leading cause of cancer-related mortality. Identifying effective drug targets is crucial for advancing LUAD treatment strategies. METHODS: This study employed proteome-wide Mendelian randomization (MR) and colocalization analyses. We collected data on 1394 plasma proteins from a protein quantitative trait loci (pQTL) study involving 4907 individuals. Genetic associations with LUAD were derived from the Transdisciplinary Research in Cancer of the Lung (TRICL) study, including 11,245 cases and 54,619 controls. We integrated pQTL and LUAD genome-wide association studies (GWASs) data to identify candidate proteins. MR utilizes single nucleotide polymorphisms (SNPs) as genetic instruments to estimate the causal effect of exposure on outcome, while Bayesian colocalization analysis determines the probability of shared causal genetic variants between traits. Our study applied these methods to assess causality between plasma proteins and LUAD. Furthermore, we employed a two-step MR to quantify the proportion of risk factors mediated by proteins on LUAD. Finally, protein-protein interaction (PPI) analysis elucidated potential links between proteins and current LUAD medications. RESULTS: We identified nine plasma proteins significantly associated with LUAD. Increased levels of ALAD, FLT1, ICAM5, and VWC2 exhibited protective effects, with odds ratios of 0.79 (95% CI 0.72-0.87), 0.39 (95% CI 0.28-0.55), 0.91 (95% CI 0.72-0.87), and 0.85 (95% CI 0.79-0.92), respectively. Conversely, MDGA2 (OR, 1.13; 95% CI 1.08-1.19), NTM (OR, 1.12; 95% CI 1.09-1.16), PMM2 (OR, 1.35; 95% CI 1.18-1.53), RNASET2 (OR, 1.15; 95% CI 1.08-1.21), and TFPI (OR, 4.58; 95% CI 3.02-6.94) increased LUAD risk. Notably, none of the nine proteins showed evidence of reverse causality. Bayesian colocalization indicated that RNASET2, TFPI, and VWC2 shared the same variant with LUAD. Furthermore, NTM and FLT1 demonstrated interactions with targets of current LUAD medications. Additionally, FLT1 and TFPI are currently under evaluation as therapeutic targets, while NTM, RNASET2, and VWC2 are potentially druggable. These findings shed light on LUAD pathogenesis, highlighting the tumor-promoting effects of RNASET2, TFPI, and NTM, along with the protective effects of VWC2 and FLT1, providing a significant biological foundation for future LUAD therapeutic targets. CONCLUSIONS: Our proteome-wide MR analysis highlighted RNASET2, TFPI, VWC2, NTM, and FLT1 as potential drug targets for further clinical investigation in LUAD. However, the specific mechanisms by which these proteins influence LUAD remain elusive. Targeting these proteins in drug development holds the potential for successful clinical trials, providing a pathway to prioritize and reduce costs in LUAD therapeutics.