Visual account of protein investment in cellular functions

Quantitative Proteomics Reveals Knockdown of CD44 Promotes Proliferation and Migration in Claudin-Low MDA-MB-231 and Hs 578T Breast Cancer Cell Lines

CD44 is a transmembrane glycoprotein that can regulate the oncogenic process. This is known to be a marker of the claudin-low subtype of breast cancer, as well as a cancer stem cell marker. However, its functional regulatory roles are poorly understood in claudin-low breast cancer. To gain comprehensive insight into the function of CD44, we performed an in-depth tandem mass tag-based proteomic analysis of two claudin-low breast cancer cell lines (MDA-MB-231 and Hs 578T) transfected with CD44 siRNA. As a result, we observed that 2736 proteins were upregulated and 2172 proteins were downregulated in CD44-knockdown MDA-MB-231 cells. For Hs 578T CD44-knockdown cells, 412 proteins were upregulated and 443 were downregulated. Gene ontology and network analyses demonstrated that the suppression of this marker mediates significant functional alterations related to oncogenic cellular processes, including proliferation, metabolism, adhesion, and gene expression regulation. A functional study confirmed that CD44 knockdown inhibited proliferation by regulating the expression of genes related to cell cycle, translation, and transcription. Moreover, this promoted the expression of multiple cell adhesion-associated proteins and attenuated cancer cell migration. Finally, our proteomic study defines the landscape of the CD44-regulated proteome of claudin-low breast cancer cells, revealing changes that mediate cell proliferation and migration. Our proteomics data set has been deposited to the ProteomeXchange Consortium via the PRIDE repository with the data set identifier PXD015171.

Cannabidiol Displays Proteomic Similarities to Antipsychotics in Cuprizone-Exposed Human Oligodendrocytic Cell Line MO3.13

Cannabidiol, a compound of Cannabis sativa, has been proposed as an alternative treatment of schizophrenia. Preclinical and clinical data have suggested that cannabidiol shares more similarity with atypical antipsychotics than typical, both of which are customarily used to manage schizophrenia symptoms. While oligodendrocytes are known to be relevant targets of antipsychotics, the biochemical knowledge in this regard is still limited. Here we evaluated the molecular pathways modulated by cannabidiol compared to the antipsychotics clozapine (atypical) and haloperidol (typical), additionally evaluating the effects of benztropine, a muscarinic receptor antagonist that displays a protective effect in oligodendrocytes and myelination. For this purpose, we employed nano-chromatography coupled with mass spectrometry to investigate the proteomic response to these drugs both in healthy oligodendrocytic cells and in a cuprizone-based toxicity model, using the human oligodendrocyte precursor cell line MO3.13. Cannabidiol shares similarities of biochemical pathways with clozapine and benztropine, in agreement with other studies that indicated an atypical antipsychotic profile. All drugs tested affected metabolic and gene expression pathways and cannabidiol, benztropine, and clozapine modulated cell proliferation and apoptosis when administered after cuprizone-induced toxicity. These general pathways are associated with cuprizone-induced cytotoxicity in MO3.13 cells, indicating a possible proteomic approach when acting against the toxic effects of cuprizone. In conclusion, although modeling oligodendrocytic cytotoxicity with cuprizone does not represent the entirety of the pathophysiology of oligodendrocyte impairments, these results provide insight into the mechanisms associated with the effects of cannabidiol and antipsychotics against cuprizone toxicity, offering new directions of study for myelin-related processes and deficits.

Saccharomyces cerevisiae Gene Expression during Fermentation of Pinot Noir Wines at an Industrially Relevant Scale

This study characterized Saccharomyces cerevisiae RC212 gene expression during Pinot noir fermentation at pilot scale (150 liters) using industry-relevant conditions. The reported gene expression patterns of RC212 are generally similar to those observed under laboratory fermentation conditions but also contain gene expression signatures related to yeast-environment interactions found in a production setting (e.g., the presence of non-Saccharomyces microorganisms).

Saccharomyces cerevisiae metabolism produces ethanol and other compounds during the fermentation of grape must into wine. Thousands of genes change expression over the course of a wine fermentation, allowing S. cerevisiae to adapt to and dominate the fermentation environment. Investigations into these gene expression patterns previously revealed genes that underlie cellular adaptation to the grape must and wine environments, involving metabolic specialization and ethanol tolerance. However, the majority of studies detailing gene expression patterns have occurred in controlled environments that may not recapitulate the biological and chemical complexity of fermentations performed at production scale. Here, an analysis of the S. cerevisiae RC212 gene expression program is presented, drawing from 40 pilot-scale fermentations (150 liters) using Pinot noir grapes from 10 California vineyards across two vintages. A core gene expression program was observed across all fermentations irrespective of vintage, similar to that of laboratory fermentations, in addition to novel gene expression patterns likely related to the presence of non-Saccharomyces microorganisms and oxygen availability during fermentation. These gene expression patterns, both common and diverse, provide insight into Saccharomyces cerevisiae biology critical to fermentation outcomes under industry-relevant conditions.

IMPORTANCE This study characterized Saccharomyces cerevisiae RC212 gene expression during Pinot noir fermentation at pilot scale (150 liters) using industry-relevant conditions. The reported gene expression patterns of RC212 are generally similar to those observed under laboratory fermentation conditions but also contain gene expression signatures related to yeast-environment interactions found in a production setting (e.g., the presence of non-Saccharomyces microorganisms). Key genes and pathways highlighted by this work remain undercharacterized, indicating the need for further research to understand the roles of these genes and their impact on industrial wine fermentation outcomes.

Genomic and proteomic profiles of biofilms on microplastics are decoupled from artificial surface properties

Microplastics in marine ecosystems are colonized by diverse prokaryotic and eukaryotic communities. How these communities and their functional profiles are shaped by the artificial surfaces remains broadly unknown. In order to close this knowledge gap, we set up an in situ experiment with pellets of the polyolefin polymer polyethylene (PE), the aromatic hydrocarbon polymer polystyrene (PS), and wooden beads along a coastal to estuarine gradient in the Baltic Sea, Germany. We used an integrated metagenomics/metaproteomics approach to evaluate the genomic potential as well as protein expression levels of aquatic plastic biofilms. Our results suggest that material properties had a minor influence on the plastic-associated assemblages, as genomic and proteomic profiles of communities associated with the structurally different polymers PE and PS were highly similar, hence polymer-unspecific. Instead, it seemed that these communities were shaped by biogeographic factors. Wood, on the other hand, induced the formation of substrate-specific biofilms and served as nutrient source itself. Our study indicates that, while PE and PS microplastics may be relevant in the photic zone as opportunistic colonization grounds for phototrophic microorganisms, they appear not to be subject to biodegradation or serve as vectors for pathogenic microorganisms in marine habitats.

Eukaryotic RNA Polymerases: The Many Ways to Transcribe a Gene

In eukaryotic cells, three nuclear RNA polymerases (RNA pols) carry out the transcription from DNA to RNA, and they all seem to have evolved from a single enzyme present in the common ancestor with archaea. The multiplicity of eukaryotic RNA pols allows each one to remain specialized in the synthesis of a subset of transcripts, which are different in the function, length, cell abundance, diversity, and promoter organization of the corresponding genes. We hypothesize that this specialization of RNA pols has conditioned the evolution of the regulatory mechanisms used to transcribe each gene subset to cope with environmental changes. We herein present the example of the homeostatic regulation of transcript levels versus changes in cell volume. We propose that the diversity and instability of messenger RNAs, transcribed by RNA polymerase II, have conditioned the appearance of regulatory mechanisms based on different gene promoter strength and mRNA stability. However, for the regulation of ribosomal RNA levels, which are very stable and transcribed mainly by RNA polymerase I from only one promoter, different mechanisms act based on gene copy variation, and a much simpler regulation of the synthesis rate.

Influence of Proteome Profiles and Intracellular Drug Exposure on Differences in CYP Activity in Donor-Matched Human Liver Microsomes and Hepatocytes

Human liver microsomes (HLM) and human hepatocytes (HH) are important in vitro systems for studies of intrinsic drug clearance (CLint) in the liver. However, the CLint values are often in disagreement for these two systems. Here, we investigated these differences in a side-by-side comparison of drug metabolism in HLM and HH prepared from 15 matched donors. Protein expression and intracellular unbound drug concentration (Kpuu) effects on the CLint were investigated for five prototypical probe substrates (bupropion-CYP2B6, diclofenac-CYP2C9, omeprazole-CYP2C19, bufuralol-CYP2D6, and midazolam-CYP3A4). The samples were donor-matched to compensate for inter-individual variability but still showed systematic differences in CLint. Global proteomics analysis outlined differences in HLM from HH and homogenates of human liver (HL), indicating variable enrichment of ER-localized cytochrome P450 (CYP) enzymes in the HLM preparation. This suggests that the HLM may not equally and accurately capture metabolic capacity for all CYPs. Scaling CLint with CYP amounts and Kpuu could only partly explain the discordance in absolute values of CLint for the five substrates. Nevertheless, scaling with CYP amounts improved the agreement in rank order for the majority of the substrates. Other factors, such as contribution of additional enzymes and variability in the proportions of active and inactive CYP enzymes in HLM and HH, may have to be considered to avoid the use of empirical scaling factors for prediction of drug metabolism.

Global Transcriptional Regulators Fine-Tune the Translational and Metabolic Efficiency for Optimal Growth of Escherichia coli

Global transcriptional regulators coordinate complex genetic interactions that bestow better adaptability for an organism against external and internal perturbations. These transcriptional regulators are known to control an enormous array of genes with diverse functionalities. However, regulator-driven molecular mechanisms that underpin precisely tuned translational and metabolic processes conducive for rapid exponential growth remain obscure. Here, we comprehensively reveal the fundamental role of global transcriptional regulators FNR, ArcA, and IHF in sustaining translational and metabolic efficiency under glucose fermentative conditions in Escherichia coli By integrating high-throughput gene expression profiles and absolute intracellular metabolite concentrations, we illustrate that these regulators are crucial in maintaining nitrogen homeostasis, govern expression of otherwise unnecessary or hedging genes, and exert tight control on metabolic bottleneck steps. Furthermore, we characterize changes in expression and activity profiles of other coregulators associated with these dysregulated metabolic pathways, determining the regulatory interactions within the transcriptional regulatory network. Such systematic findings emphasize their importance in optimizing the proteome allocation toward metabolic enzymes as well as ribosomes, facilitating condition-specific phenotypic outcomes. Consequentially, we reveal that disruption of this inherent trade-off between ribosome and metabolic proteome economy due to the loss of regulators resulted in lowered growth rates. Moreover, our findings reinforce that the accumulations of intracellular metabolites in the event of proteome repartitions negatively affects the glucose uptake. Overall, by extending the three-partition proteome allocation theory concordant with multi-omics measurements, we elucidate the physiological consequences of loss of global regulators on central carbon metabolism restraining the organism to attain maximal biomass synthesis.IMPORTANCE Cellular proteome allocation in response to environmental or internal perturbations governs their eventual phenotypic outcome. This entails striking an effective balance between amino acid biosynthesis by metabolic proteins and its consumption by ribosomes. However, the global transcriptional regulator-driven molecular mechanisms that underpin their coordination remains unexplored. Here, we emphasize that global transcriptional regulators, known to control expression of a myriad of genes, are fundamental for precisely tuning the translational and metabolic efficiencies that define the growth optimality. Towards this, we systematically characterized the single deletion effect of FNR, ArcA, and IHF regulators of Escherichia coli on exponential growth under anaerobic glucose fermentative conditions. Their absence disrupts the stringency of proteome allocation, which manifests as impairment in key metabolic processes and an accumulation of intracellular metabolites. Furthermore, by incorporating an extension to the empirical growth laws, we quantitatively demonstrate the general design principles underlying the existence of these regulators in E. coli.

Estimating the number of protein molecules in a plant cell: protein and amino acid homeostasis during drought

During drought stress, cellular proteostasis on the one hand and amino acid homeostasis on the other hand are severely challenged, because the decrease in photosynthesis induces massive proteolysis, leading to drastic changes in both the proteome and the free amino acid pool. Thus, we selected progressive drought stress in Arabidopsis (Arabidopsis thaliana) as a model to investigate on a quantitative level the balance between protein and free amino acid homeostasis. We analyzed the mass composition of the leaf proteome based on proteomics datasets, and estimated how many protein molecules are present in a plant cell and its subcellular compartments. In addition, we calculated stress-induced changes in the distribution of individual amino acids between the free and protein-bound pools. Under control conditions, an average Arabidopsis mesophyll cell contains about 25 billion protein molecules, of which 80% are localized in chloroplasts. Severe water deficiency leads to degradation of more than 40% of the leaf protein mass, and thus causes a drastic shift in distribution toward the free amino acid pool. Stress-induced proteolysis of just half of the 340 million RubisCO hexadecamers present in the chloroplasts of a single mesophyll cell doubles the cellular content of free amino acids. A major fraction of the amino acids released from proteins is channeled into synthesis of proline, which is a compatible osmolyte. Complete oxidation of the remaining fraction as an alternative respiratory substrate can fully compensate for the lack of photosynthesis-derived carbohydrates for several hours.

Corynebacterium diphtheriae Proteome Adaptation to Cell Culture Medium and Serum

Host-pathogen interactions are often studied in vitro using primary or immortal cell lines. This set-up avoids ethical problems of animal testing and has the additional advantage of lower costs. However, the influence of cell culture media on bacterial growth and metabolism is not considered or investigated in most cases. To address this question growth and proteome adaptation of Corynebacterium diphtheriae strain ISS3319 were investigated in this study. Bacteria were cultured in standard growth medium, cell culture medium, and fetal calf serum. Mass spectrometric analyses and label-free protein quantification hint at an increased bacterial pathogenicity when grown in cell culture medium as well as an influence of the growth medium on the cell envelope.

Autosomal recessive variants in TUBGCP2 alter the γ-tubulin ring complex leading to neurodevelopmental disease

Microtubules help building the cytoskeleton of neurons and other cells. Several components of the gamma-tubulin (γ-tubulin) complex have been previously reported in human neurodevelopmental diseases. We describe two siblings from a consanguineous Turkish family with dysmorphic features, developmental delay, brain malformation, and epilepsy carrying a homozygous mutation (p.Glu311Lys) in TUBGCP2 encoding the γ-tubulin complex 2 (GCP2) protein. This variant is predicted to disrupt the electrostatic interaction of GCP2 with GCP3. In primary fibroblasts carrying the variant, we observed a faint delocalization of γ-tubulin during the cell cycle but normal GCP2 protein levels. Through mass spectrometry, we observed dysregulation of multiple proteins involved in the assembly and organization of the cytoskeleton and the extracellular matrix, controlling cellular adhesion and of proteins crucial for neuronal homeostasis including axon guidance. In summary, our functional and proteomic studies link TUBGCP2 and the γ-tubulin complex to the development of the central nervous system in humans.

Translational landscape and protein biogenesis demands of the early secretory pathway in Komagataella phaffii

Background

Eukaryotes use distinct networks of biogenesis factors to synthesize, fold, monitor, traffic, and secrete proteins. During heterologous expression, saturation of any of these networks may bottleneck titer and yield. To understand the flux through various routes into the early secretory pathway, we quantified the global and membrane-associated translatomes of Komagataella phaffii.

Results

By coupling Ribo-seq with long-read mRNA sequencing, we generated a new annotation of protein-encoding genes. By using Ribo-seq with subcellular fractionation, we quantified demands on co- and posttranslational translocation pathways. During exponential growth in rich media, protein components of the cell-wall represent the greatest number of nascent chains entering the ER. Transcripts encoding the transmembrane protein PMA1 sequester more ribosomes at the ER membrane than any others. Comparison to Saccharomyces cerevisiae reveals conservation in the resources allocated by gene ontology, but variation in the diversity of gene products entering the secretory pathway.

Conclusion

A subset of host proteins, particularly cell-wall components, impose the greatest biosynthetic demands in the early secretory pathway. These proteins are potential targets in strain engineering aimed at alleviating bottlenecks during heterologous protein production.

CIITA-Transduced Glioblastoma Cells Uncover a Rich Repertoire of Clinically Relevant Tumor-Associated HLA-II Antigens

CD4+ T cell responses are crucial for inducing and maintaining effective anticancer immunity, and the identification of human leukocyte antigen class II (HLA-II) cancer-specific epitopes is key to the development of potent cancer immunotherapies. In many tumor types, and especially in glioblastoma (GBM), HLA-II complexes are hardly ever naturally expressed. Hence, little is known about immunogenic HLA-II epitopes in GBM. With stable expression of the class II major histocompatibility complex transactivator (CIITA) coupled to a detailed and sensitive mass spectrometry-based immunopeptidomics analysis, we here uncovered a remarkable breadth of the HLA-ligandome in HROG02, HROG17, and RA GBM cell lines. The effect of CIITA expression on the induction of the HLA-II presentation machinery was striking in each of the three cell lines, and it was significantly higher compared with interferon gamma (IFNɣ) treatment. In total, we identified 16,123 unique HLA-I peptides and 32,690 unique HLA-II peptides. In order to genuinely define the identified peptides as true HLA ligands, we carefully characterized their association with the different HLA allotypes. In addition, we identified 138 and 279 HLA-I and HLA-II ligands, respectively, most of which are novel in GBM, derived from known GBM-associated tumor antigens that have been used as source proteins for a variety of GBM vaccines. Our data further indicate that CIITA-expressing GBM cells acquired an antigen presenting cell-like phenotype as we found that they directly present external proteins as HLA-II ligands. Not only that CIITA-expressing GBM cells are attractive models for antigen discovery endeavors, but also such engineered cells have great therapeutic potential through massive presentation of a diverse antigenic repertoire.

Utilization of Laser Capture Microdissection Coupled to Mass Spectrometry to Uncover the Proteome of Cellular Protrusions

Laser capture microdissection (LCM) provides a fast, specific, and versatile method to isolate and enrich cells in mixed populations and/or subcellular structures, for further proteomic study. Furthermore, mass spectrometry (MS) can quickly and accurately generate differential protein expression profiles from small amounts of samples. Although cellular protrusions-such as tunneling nanotubes, filopodia, growth cones, invadopodia, etc.-are involved in essential physiological and pathological actions such as phagocytosis or cancer-cell invasion, the study of their protein composition is progressing slowly due to their fragility and transient nature. The method described herein, combining LCM and MS, has been designed to identify the proteome of different cellular protrusions. First, cells are fixed with a novel fixative method to preserve the cellular protrusions, which are isolated by LCM. Next, the extraction of proteins from the enriched sample is optimized to de-crosslink the fixative agent to improve the identification of proteins by MS. The efficient protein recovery and high sample quality of this method enable the protein profiling of these small and diverse subcellular structures.

Single-cell omics analyses with single molecular detection: challenges and perspectives

The ultimate goal of single-cell analyses is to obtain the biomolecular content for each cell in unicellular and multicellular organisms at different points of their life cycle under variable environmental conditions. These require an assessment of: a) the total number of cells, b) the total number of cell types, and c) the complete and quantitative single molecular detection and identification for all classes of biopolymers, and organic and inorganic compounds, in each individual cell. For proteins, glycans, lipids, and metabolites, whose sequences cannot be amplified by copying as in the case of nucleic acids, the detection limit by mass spectrometry is about 10⁵ molecules. Therefore, proteomic, glycomic, lipidomic, and metabolomic analyses do not yet permit the assembly of the complete single-cell omes. The construction of novel nanoelectrophoretic arrays and nano in microarrays on a single 1-cm-diameter chip has shown proof of concept for a high throughput platform for parallel processing of thousands of individual cells. Combined with dynamic secondary ion mass spectrometry, with 3D scanning capability and lateral resolution of 50 nm, the sensitivity of single molecular quantification and identification for all classes of biomolecules could be reached. Further development and routine application of such technological and instrumentation solution would allow assembly of complete omes with a quantitative assessment of structural and functional cellular diversity at the molecular level.

The diversity of Shine-Dalgarno sequences sheds light on the evolution of translation initiation

Shine-Dalgarno (SD) sequences, the core element of prokaryotic ribosome-binding sites, facilitate mRNA translation by base-pair interaction with the anti-SD (aSD) sequence of 16S rRNA. In contrast to this paradigm, an inspection of thousands of prokaryotic species unravels tremendous SD sequence diversity both within and between genomes, whereas aSD sequences remain largely static. The pattern has led many to suggest unidentified mechanisms for translation initiation. Here we review known translation-initiation pathways in prokaryotes. Moreover, we seek to understand the cause and consequence of SD diversity through surveying recent advances in biochemistry, genomics, and high-throughput genetics. These findings collectively show: (1) SD:aSD base pairing is beneficial but nonessential to translation initiation. (2) The 5' untranslated region of mRNA evolves dynamically and correlates with organismal phylogeny and ecological niches. (3) Ribosomes have evolved distinct usage of translation-initiation pathways in different species. We propose a model portraying the SD diversity shaped by optimization of gene expression, adaptation to environments and growth demands, and the species-specific prerequisite of ribosomes to initiate translation. The model highlights the coevolution of ribosomes and mRNA features, leading to functional customization of the translation apparatus in each organism.

Fecal microbiota transplant promotes response in immunotherapy-refractory melanoma patients

The gut microbiome has been shown to influence the response of tumors to anti-PD-1 (programmed cell death-1) immunotherapy in preclinical mouse models and observational patient cohorts. However, modulation of gut microbiota in cancer patients has not been investigated in clinical trials. In this study, we performed a phase 1 clinical trial to assess the safety and feasibility of fecal microbiota transplantation (FMT) and reinduction of anti-PD-1 immunotherapy in 10 patients with anti-PD-1-refractory metastatic melanoma. We observed clinical responses in three patients, including two partial responses and one complete response. Notably, treatment with FMT was associated with favorable changes in immune cell infiltrates and gene expression profiles in both the gut lamina propria and the tumor microenvironment. These early findings have implications for modulating the gut microbiota in cancer treatment.

Proteomic Characterization of Synaptosomes from Human Substantia Nigra Indicates Altered Mitochondrial Translation in Parkinson's Disease

The pathological hallmark of Parkinson's disease (PD) is the loss of neuromelanin-containing dopaminergic neurons within the substantia nigra pars compacta (SNpc). Additionally, numerous studies indicate an altered synaptic function during disease progression. To gain new insights into the molecular processes underlying the alteration of synaptic function in PD, a proteomic study was performed. Therefore, synaptosomes were isolated by density gradient centrifugation from SNpc tissue of individuals at advanced PD stages (N = 5) as well as control subjects free of pathology (N = 5) followed by mass spectrometry-based analysis. In total, 362 proteins were identified and assigned to the synaptosomal core proteome. This core proteome comprised all proteins expressed within the synapses without regard to data analysis software, gender, age, or disease. The differential analysis between control subjects and PD cases revealed that CD9 antigen was overrepresented and fourteen proteins, among them Thymidine kinase 2 (TK2), mitochondrial, 39S ribosomal protein L37, neurolysin, and Methionine-tRNA ligase (MARS2) were underrepresented in PD suggesting an alteration in mitochondrial translation within synaptosomes.

Integrative characterization of the near-minimal bacterium Mesoplasma florum

The near-minimal bacterium Mesoplasma florum is an interesting model for synthetic genomics and systems biology due to its small genome (~ 800 kb), fast growth rate, and lack of pathogenic potential. However, fundamental aspects of its biology remain largely unexplored. Here, we report a broad yet remarkably detailed characterization of M. florum by combining a wide variety of experimental approaches. We investigated several physical and physiological parameters of this bacterium, including cell size, growth kinetics, and biomass composition of the cell. We also performed the first genome-wide analysis of its transcriptome and proteome, notably revealing a conserved promoter motif, the organization of transcription units, and the transcription and protein expression levels of all protein-coding sequences. We converted gene transcription and expression levels into absolute molecular abundances using biomass quantification results, generating an unprecedented view of the M. florum cellular composition and functions. These characterization efforts provide a strong experimental foundation for the development of a genome-scale model for M. florum and will guide future genome engineering endeavors in this simple organism.

Exoproteomic profiling uncovers critical determinants for virulence of livestock-associated and human-originated Staphylococcus aureus ST398 strains

Staphylococcus aureus: with the sequence type (ST) 398 was previously associated with livestock carriage. However, in recent years livestock-independent S. aureus ST398 has emerged, representing a potential health risk for humans especially in nosocomial settings. Judged by whole-genome sequencing analyses, the livestock- and human originated strains belong to two different S. aureus ST398 clades but, to date, it was not known to what extent these clades differ in terms of actual virulence. Therefore, the objective of this study was to profile the exoproteomes of 30 representative S. aureus ST398 strains by mass spectrometry, to assess clade-specific differences in virulence factor secretion, and to correlate the identified proteins and their relative abundance to the strains' actual virulence. Although the human-originated strains are more heterogeneous at the genome level, our observations show that they are more homogeneous in terms of virulence factor production than the livestock-associated strains. To assess differences in virulence, infection models based on larvae of the wax moth Galleria mellonella and the human HeLa cell line were applied. Correlation of the exoproteome data to larval killing and toxicity toward HeLa cells uncovered critical roles of the staphylococcal Sbi, SpA, SCIN and CHIPS proteins in virulence. These findings were validated by showing that sbi or spa mutant bacteria are attenuated in G. mellonella and that the purified SCIN and CHIPS proteins are toxic for HeLa cells. Altogether, we show that exoproteome profiling allows the identification of critical determinants for virulence of livestock-associated and human-originated S. aureus ST398 strains.

Influence of metabolic status and genetic merit for fertility on proteomic composition of bovine oviduct fluid†

The oviduct plays a crucial role in fertilization and early embryo development providing the microenvironment for oocyte, spermatozoa, and early embryo. Since dairy cow fertility declined steadily over the last decades, reasons for early embryonic loss have gained increasing interest. Analyzing two animal models, this study aimed to investigate the impact of genetic predisposition for fertility and of metabolic stress on the protein composition of oviduct fluid. A metabolic model comprised maiden Holstein heifers and postpartum lactating (Lact) and non-lactating (Dry) cows, while a genetic model consisted of heifers from the Montbéliarde breed and Holstein heifers with low- and high-fertility index. In a holistic proteomic analysis of oviduct fluid from all groups using nano-liquid chromatography tandem-mass spectrometry analysis and label-free quantification, we were able to identify 1976 proteins, among which 143 showed abundance alterations in the pairwise comparisons within both models. Most differentially abundant proteins were revealed between low fertility Holstein and Montbéliarde (52) in the genetic model and between lactating and maiden Holstein (19) in the metabolic model, demonstrating a substantial effect of genetic predisposition for fertility and metabolic stress on the oviduct fluid proteome. Functional classification of affected proteins revealed actin binding, translation, and immune system processes as prominent gene ontology (GO) clusters. Notably, Actin-related protein 2/3 complex subunit 1B and the three immune system-related proteins SERPIND1 protein, immunoglobulin kappa locus protein, and Alpha-1-acid glycoprotein were affected in both models, suggesting that abundance changes of immune-related proteins in oviduct fluid play an important role for early embryonic loss.

Staphylococcus aureus ATP Synthase Promotes Biofilm Persistence by Influencing Innate Immunity

Staphylococcus aureus is a major cause of prosthetic joint infection (PJI), which is characterized by biofilm formation. S. aureus biofilm skews the host immune response toward an anti-inflammatory profile by the increased recruitment of myeloid-derived suppressor cells (MDSCs) that attenuate macrophage proinflammatory activity, leading to chronic infection. A screen of the Nebraska Transposon Mutant Library identified several hits in the ATP synthase operon that elicited a heightened inflammatory response in macrophages and MDSCs, including atpA, which encodes the alpha subunit of ATP synthase. An atpA transposon mutant (ΔatpA) had altered growth kinetics under both planktonic and biofilm conditions, along with a diffuse biofilm architecture that was permissive for leukocyte infiltration, as observed by confocal laser scanning microscopy. Coculture of MDSCs and macrophages with ΔatpA biofilm elicited significant increases in the proinflammatory cytokines interleukin 12p70 (IL-12p70), tumor necrosis factor alpha (TNF-α), and IL-6. This was attributed to increased leukocyte survival resulting from less toxin and protease production by ΔatpA biofilm as determined by liquid chromatography with tandem mass spectrometry (LC-MS/MS). The enhanced inflammatory response elicited by ΔatpA biofilm was cell lysis-dependent since it was negated by polyanethole sodium sulfanate treatment or deletion of the major autolysin, Atl. In a mouse model of PJI, ΔatpA-infected mice had decreased MDSCs concomitant with increased monocyte/macrophage infiltrates and proinflammatory cytokine production, which resulted in biofilm clearance. These studies identify S. aureus ATP synthase as an important factor in influencing the immune response during biofilm-associated infection and bacterial persistence.IMPORTANCE Medical device-associated biofilm infections are a therapeutic challenge based on their antibiotic tolerance and ability to evade immune-mediated clearance. The virulence determinants responsible for bacterial biofilm to induce a maladaptive immune response remain largely unknown. This study identified a critical role for S. aureus ATP synthase in influencing the host immune response to biofilm infection. An S. aureus ATP synthase alpha subunit mutant (ΔatpA) elicited heightened proinflammatory cytokine production by leukocytes in vitro and in vivo, which coincided with improved biofilm clearance in a mouse model of prosthetic joint infection. The ability of S. aureus ΔatpA to augment host proinflammatory responses was cell lysis-dependent, as inhibition of bacterial lysis by polyanethole sodium sulfanate or a ΔatpAΔatl biofilm did not elicit heightened cytokine production. These studies reveal a critical role for AtpA in shaping the host immune response to S. aureus biofilm.

Integrated Framework of the Immune-Defense Transcriptional Signatures in the Arabidopsis Shoot Apical Meristem

The growing tips of plants grow sterile; therefore, disease-free plants can be generated from them. How plants safeguard growing apices from pathogen infection is still a mystery. The shoot apical meristem (SAM) is one of the three stem cells niches that give rise to the above ground plant organs. This is very well explored; however, how signaling networks orchestrate immune responses against pathogen infections in the SAM remains unclear. To reconstruct a transcriptional framework of the differentially expressed genes (DEGs) pertaining to various SAM cellular populations, we acquired large-scale transcriptome datasets from the public repository Gene Expression Omnibus (GEO). We identify here distinct sets of genes for various SAM cellular populations that are enriched in immune functions, such as immune defense, pathogen infection, biotic stress, and response to salicylic acid and jasmonic acid and their biosynthetic pathways in the SAM. We further linked those immune genes to their respective proteins and identify interactions among them by mapping a transcriptome-guided SAM-interactome. Furthermore, we compared stem-cells regulated transcriptome with innate immune responses in plants showing transcriptional separation among their DEGs in Arabidopsis. Besides unleashing a repertoire of immune-related genes in the SAM, our analysis provides a SAM-interactome that will help the community in designing functional experiments to study the specific defense dynamics of the SAM-cellular populations. Moreover, our study promotes the essence of large-scale omics data re-analysis, allowing a fresh look at the SAM-cellular transcriptome repurposing data-sets for new questions.

Modeling microbial metabolic trade-offs in a chemostat

Microbes face intense competition in the natural world, and so need to wisely allocate their resources to multiple functions, in particular to metabolism. Understanding competition among metabolic strategies that are subject to trade-offs is therefore crucial for deeper insight into the competition, cooperation, and community assembly of microorganisms. In this work, we evaluate competing metabolic strategies within an ecological context by considering not only how the environment influences cell growth, but also how microbes shape their chemical environment. Utilizing chemostat-based resource-competition models, we exhibit a set of intuitive and general procedures for assessing metabolic strategies. Using this framework, we are able to relate and unify multiple metabolic models, and to demonstrate how the fitness landscape of strategies becomes intrinsically dynamic due to species-environment feedback. Such dynamic fitness landscapes produce rich behaviors, and prove to be crucial for ecological and evolutionarily stable coexistence in all the models we examined.

Highly parallel lab evolution reveals that epistasis can curb the evolution of antibiotic resistance

Genetic perturbations that affect bacterial resistance to antibiotics have been characterized genome-wide, but how do such perturbations interact with subsequent evolutionary adaptation to the drug? Here, we show that strong epistasis between resistance mutations and systematically identified genes can be exploited to control spontaneous resistance evolution. We evolved hundreds of Escherichia coli K-12 mutant populations in parallel, using a robotic platform that tightly controls population size and selection pressure. We find a global diminishing-returns epistasis pattern: strains that are initially more sensitive generally undergo larger resistance gains. However, some gene deletion strains deviate from this general trend and curtail the evolvability of resistance, including deletions of genes for membrane transport, LPS biosynthesis, and chaperones. Deletions of efflux pump genes force evolution on inferior mutational paths, not explored in the wild type, and some of these essentially block resistance evolution. This effect is due to strong negative epistasis with resistance mutations. The identified genes and cellular functions provide potential targets for development of adjuvants that may block spontaneous resistance evolution when combined with antibiotics.

Contextual Flexibility in Pseudomonas aeruginosa Central Carbon Metabolism during Growth in Single Carbon Sources

Pseudomonas aeruginosa is an opportunistic human pathogen that is well known for causing infections in the airways of people with cystic fibrosis. Although it is clear that P. aeruginosa is metabolically well adapted to life in the CF lung, little is currently known about how the organism metabolizes the nutrients available in the airways. In this work, we used a combination of gene expression and isotope tracer (“fluxomic”) analyses to find out exactly where the input carbon goes during growth on two CF-relevant carbon sources, acetate and glycerol (derived from the breakdown of lung surfactant). We found that carbon is routed (“fluxed”) through very different pathways during growth on these substrates and that this is accompanied by an unexpected remodeling of the cell’s electron transfer pathways. Having access to this “blueprint” is important because the metabolism of P. aeruginosa is increasingly being recognized as a target for the development of much-needed antimicrobial agents.

Pseudomonas aeruginosa is an opportunistic human pathogen, particularly noted for causing infections in the lungs of people with cystic fibrosis (CF). Previous studies have shown that the gene expression profile of P. aeruginosa appears to converge toward a common metabolic program as the organism adapts to the CF airway environment. However, we still have only a limited understanding of how these transcriptional changes impact metabolic flux at the systems level. To address this, we analyzed the transcriptome, proteome, and fluxome of P. aeruginosa grown on glycerol or acetate. These carbon sources were chosen because they are the primary breakdown products of an airway surfactant, phosphatidylcholine, which is known to be a major carbon source for P. aeruginosa in CF airways. We show that the fluxes of carbon throughout central metabolism are radically different among carbon sources. For example, the newly recognized “EDEMP cycle” (which incorporates elements of the Entner-Doudoroff [ED] pathway, the Embden-Meyerhof-Parnas [EMP] pathway, and the pentose phosphate [PP] pathway) plays an important role in supplying NADPH during growth on glycerol. In contrast, the EDEMP cycle is attenuated during growth on acetate, and instead, NADPH is primarily supplied by the reaction catalyzed by isocitrate dehydrogenase(s). Perhaps more importantly, our proteomic and transcriptomic analyses revealed a global remodeling of gene expression during growth on the different carbon sources, with unanticipated impacts on aerobic denitrification, electron transport chain architecture, and the redox economy of the cell. Collectively, these data highlight the remarkable metabolic plasticity of P. aeruginosa; that plasticity allows the organism to seamlessly segue between different carbon sources, maximizing the energetic yield from each.

Ribosome assembly factor Adenylate Kinase 6 maintains cell proliferation and cell size homeostasis during root growth

From the cellular perspective, organ growth is determined by production and growth of cells. Uncovering how these two processes are coordinated is essential for understanding organogenesis and regulation of organ growth. We utilized phenotypic and genetic variation of 252 natural accessions of Arabidopsis thaliana to conduct genome-wide association studies (GWAS) for identifying genes underlying root growth variation; using a T-DNA line candidate approach, we identified one gene involved in root growth control and characterized its function using microscopy, root growth kinematics, G2/M phase cell count, ploidy levels and ribosome polysome profiles. We identified a factor contributing to root growth control: Arabidopsis Adenylate Kinase 6 (AAK6). AAK6 is required for normal cell production and normal cell elongation, and its natural genetic variation is involved in determining root growth differences between Arabidopsis accessions. A lack of AAK6 reduces cell production in the aak6 root apex, but this is partially compensated for by longer mature root cells. Thereby, aak6 mutants exhibit compensatory cell enlargement, a phenomenon unexpected in roots. Moreover, aak6 plants accumulate 80S ribosomes while the polysome profile remains unchanged, consistent with a phenotype of perturbed ribosome biogenesis. In conclusion, AAK6 impacts ribosome abundance, cell production and thereby root growth.

Amino acids are key substrates to Escherichia coli BW25113 for achieving high specific growth rate

Studying substrate consumption in nutrient-rich conditions is challenging because often the growth medium includes undefined components like yeast extract or peptone. For clear and consistent results, it is necessary to use defined medium, where substrate utilization can be followed. In the present work, Escherichia coli BW25113 batch growth in a medium supplemented with 20 proteinogenic amino acids and glucose was studied. Focus was on the quantitative differences in substrate consumption and proteome composition between minimal and nutrient-rich medium. In the latter, 72% of carbon used for biomass growth came from amino acids and 28% from glucose. Serine was identified as the most consumed substrate with 41% of total carbon consumption. Proteome comparison between nutrient-rich and minimal medium revealed changes in TCA cycle and acetate producing enzymes that together with extracellular metabolite data pointed to serine being consumed mainly for energy generation purposes. Serine removal from the growth medium decreased specific growth rate by 22%. In addition, proteome comparison between media revealed a large shift in amino acid synthesis and translation related proteins. Overall, this work describes in quantitative terms the batch growth carbon uptake profile and proteome allocation of E. coli BW25113 in minimal and nutrient-rich medium.

The ETFL formulation allows multi-omics integration in thermodynamics-compliant metabolism and expression models

Systems biology has long been interested in models capturing both metabolism and expression in a cell. We propose here an implementation of the metabolism and expression model formalism (ME-models), which we call ETFL, for Expression and Thermodynamics Flux models. ETFL is a hierarchical model formulation, from metabolism to RNA synthesis, that allows simulating thermodynamics-compliant intracellular fluxes as well as enzyme and mRNA concentration levels. ETFL formulates a mixed-integer linear problem (MILP) that enables both relative and absolute metabolite, protein, and mRNA concentration integration. ETFL is compatible with standard MILP solvers and does not require a non-linear solver, unlike the previous state of the art. It also accounts for growth-dependent parameters, such as relative protein or mRNA content. We present ETFL along with its validation using results obtained from a well-characterized E. coli model. We show that ETFL is able to reproduce proteome-limited growth. We also subject it to several analyses, including the prediction of feasible mRNA and enzyme concentrations and gene essentiality.

Accounting for the effects of genetic expression in genome-scale metabolic models is challenging. Here, the authors introduce a model formulation that efficiently simulates thermodynamic-compliant fluxes, enzyme and mRNA concentration levels, allowing omics integration and broad analysis of in silico cellular physiology.

Phenotypic proteomic profiling identifies a landscape of targets for circadian clock-modulating compounds

This study provides comprehensive insights into the mechanism of action and cellular effects of circadian period–modulating compounds, which is critical for clearly defining molecular targets to modulate daily rhythms for therapeutic benefit.

Determining the exact targets and mechanisms of action of drug molecules that modulate circadian rhythms is critical to develop novel compounds to treat clock-related disorders. Here, we have used phenotypic proteomic profiling (PPP) to systematically determine molecular targets of four circadian period–lengthening compounds in human cells. We demonstrate that the compounds cause similar changes in phosphorylation and activity of several proteins and kinases involved in vital pathways, including MAPK, NGF, B-cell receptor, AMP-activated protein kinases (AMPKs), and mTOR signaling. Kinome profiling further indicated inhibition of CKId, ERK1/2, CDK2/7, TNIK, and MST4 kinases as a common mechanism of action for these clock-modulating compounds. Pharmacological or genetic inhibition of several convergent kinases lengthened circadian period, establishing them as novel circadian targets. Finally, thermal stability profiling revealed binding of the compounds to clock regulatory kinases, signaling molecules, and ubiquitination proteins. Thus, phenotypic proteomic profiling defines novel clock effectors that could directly inform precise therapeutic targeting of the circadian system in humans.

Homeostasis in the Central Dogma of molecular biology: the importance of mRNA instability

Cell survival requires the control of biomolecule concentration, i.e. biomolecules should approach homeostasis. With information-carrying macromolecules, the particular concentration variation ranges depend on each type: DNA is not buffered, but mRNA and protein concentrations are homeostatically controlled, which leads to the ribostasis and proteostasis concepts. In recent years, we have studied the particular features of mRNA ribostasis and proteostasis in the model organism S. cerevisiae. Here we extend this study by comparing published data from three other model organisms: E. coli, S. pombe and cultured human cells. We describe how mRNA ribostasis is less strict than proteostasis. A constant ratio appears between the average decay and dilution rates during cell growth for mRNA, but not for proteins. We postulate that this is due to a trade-off between the cost of synthesis and the response capacity. This compromise takes place at the transcription level, but is not possible at the translation level as the high stability of proteins, versus that of mRNAs, precludes it. We hypothesize that the middle-place role of mRNA in the Central Dogma of Molecular Biology and its chemical instability make it more suitable than proteins for the fast changes needed for gene regulation.

Fast and Accurate Bacterial Species Identification in Urine Specimens Using LC-MS/MS Mass Spectrometry and Machine Learning

Fast identification of microbial species in clinical samples is essential to provide an appropriate antibiotherapy to the patient and reduce the prescription of broad-spectrum antimicrobials leading to antibioresistances. MALDI-TOF-MS technology has become a tool of choice for microbial identification but has several drawbacks: it requires a long step of bacterial culture before analysis (≥24 h), has a low specificity and is not quantitative. We developed a new strategy for identifying bacterial species in urine using specific LC-MS/MS peptidic signatures. In the first training step, libraries of peptides are obtained on pure bacterial colonies in DDA mode, their detection in urine is then verified in DIA mode, followed by the use of machine learning classifiers (NaiveBayes, BayesNet and Hoeffding tree) to define a peptidic signature to distinguish each bacterial species from the others. Then, in the second step, this signature is monitored in unknown urine samples using targeted proteomics. This method, allowing bacterial identification in less than 4 h, has been applied to fifteen species representing 84% of all Urinary Tract Infections. More than 31,000 peptides in 190 samples were quantified by DIA and classified by machine learning to determine an 82 peptides signature and build a prediction model. This signature was validated for its use in routine using Parallel Reaction Monitoring on two different instruments. Linearity and reproducibility of the method were demonstrated as well as its accuracy on donor specimens. Within 4h and without bacterial culture, our method was able to predict the predominant bacteria infecting a sample in 97% of cases and 100% above the standard threshold. This work demonstrates the efficiency of our method for the rapid and specific identification of the bacterial species causing UTI and could be extended in the future to other biological specimens and to bacteria having specific virulence or resistance factors.

Proteogenomics of Colorectal Cancer Liver Metastases: Complementing Precision Oncology with Phenotypic Data

Hotspot testing for activating KRAS mutations is used in precision oncology to select colorectal cancer (CRC) patients who are eligible for anti-EGFR treatment. However, even for KRAS^wildtype tumors anti-EGFR response rates are <30%, while mutated-KRAS does not entirely rule out response, indicating the need for improved patient stratification. We performed proteogenomic phenotyping of KRAS^wildtype and KRAS^G12V CRC liver metastases (mCRC). Among >9000 proteins we detected considerable expression changes including numerous proteins involved in progression and resistance in CRC. We identified peptides representing a number of predicted somatic mutations, including KRAS^G12V. For eight of these, we developed a multiplexed parallel reaction monitoring (PRM) mass spectrometry assay to precisely quantify the mutated and canonical protein variants. This allowed phenotyping of eight mCRC tumors and six paired healthy tissues, by determining mutation rates on the protein level. Total KRAS expression varied between tumors (0.47–1.01 fmol/µg total protein) and healthy tissues (0.13–0.64 fmol/µg). In KRAS^G12V-mCRC, G12V-mutation levels were 42–100%, while one patient had only 10% KRAS^G12V but 90% KRAS^wildtype. This might represent a missed therapeutic opportunity: based on hotspot sequencing, the patient was excluded from anti-EGFR treatment and instead received chemotherapy, while PRM-based tumor-phenotyping indicates the patient might have benefitted from anti-EGFR therapy.

Dissecting the Shared and Context-Dependent Pathways Mediated by the p140Cap Adaptor Protein in Cancer and in Neurons

The p140Cap adaptor protein is a scaffold molecule physiologically expressed in few epithelial tissues, such as the mammary gland, and in differentiated neurons. While the role of p140Cap in mammary gland epithelia is not still understood, we already know that a significant subset of breast cancers express p140Cap. In the subgroup of ERBB2-amplified breast cancers, a high p140Cap status predicts a significantly lower probability of developing a distant event and a clear difference in survival. p140Cap is causal in dampening ERBB2-positive tumor cell progression, impairing tumor onset and growth, and counteracting epithelial mesenchymal transition, resulting in decreased metastasis formation. Since only a few p140Cap interacting proteins have been identified in breast cancer and the molecular complexes and pathways underlying the cancer function of p140Cap are largely unknown, we generated a p140Cap interactome from ERBB2-positive breast cancer cells, identifying cancer specific components and those shared with the synaptic interactome. We identified 373 interacting proteins in cancer cells, including those with functions relevant to cell adhesion, protein homeostasis, regulation of cell cycle and apoptosis, which are frequently deregulated in cancer. Within the interactome, we identified 15 communities (clusters) with topology-functional relationships. In neurons, where p140Cap is key in regulating synaptogenesis, synaptic transmission and synaptic plasticity, it establishes an extensive interactome with proteins that cluster to sub complexes located in the postsynaptic density. p140Cap interactors converge on key synaptic processes, including synaptic transmission, actin cytoskeleton remodeling and cell-cell junction organization. Comparing the breast cancer to the synaptic interactome, we found 39 overlapping proteins, a relatively small overlap. However, cell adhesion and remodeling of actin cytoskeleton clearly emerge as common terms in the shared subset. Thus, the functional signature of the two interactomes is primarily determined by organ/tissue and functional specificity, while the overlap provides a list of shared functional terms, which might be linked to both cancer and neurological functions.

Proteomics of Melanoma Response to Immunotherapy Reveals Mitochondrial Dependence

Immunotherapy has revolutionized cancer treatment, yet most patients do not respond. Here, we investigated mechanisms of response by profiling the proteome of clinical samples from advanced stage melanoma patients undergoing either tumor infiltrating lymphocyte (TIL)-based or anti- programmed death 1 (PD1) immunotherapy. Using high-resolution mass spectrometry, we quantified over 10,300 proteins in total and ∼4,500 proteins across most samples in each dataset. Statistical analyses revealed higher oxidative phosphorylation and lipid metabolism in responders than in non-responders in both treatments. To elucidate the effects of the metabolic state on the immune response, we examined melanoma cells upon metabolic perturbations or CRISPR-Cas9 knockouts. These experiments indicated lipid metabolism as a regulatory mechanism that increases melanoma immunogenicity by elevating antigen presentation, thereby increasing sensitivity to T cell mediated killing both in vitro and in vivo. Altogether, our proteomic analyses revealed association between the melanoma metabolic state and the response to immunotherapy, which can be the basis for future improvement of therapeutic response.

Spatial sorting enables comprehensive characterization of liver zonation

The mammalian liver is composed of repeating hexagonal units termed lobules. Spatially resolved single-cell transcriptomics revealed that about half of hepatocyte genes are differentially expressed across the lobule, yet technical limitations impeded reconstructing similar global spatial maps of other hepatocyte features. Here, we show how zonated surface markers can be used to sort hepatocytes from defined lobule zones with high spatial resolution. We apply transcriptomics, miRNA array measurements and mass spectrometry proteomics to reconstruct spatial atlases of multiple zonated features. We demonstrate that protein zonation largely overlaps with mRNA zonation, with the periportal HNF4α as an exception. We identify zonation of miRNAs such as miR-122, and inverse zonation of miRNAs and their hepatocyte target genes, highlighting potential regulation of protein levels through zonated mRNA degradation. Among the targets we find the pericentral Wnt receptors Fzd7 and Fzd8 and the periportal Wnt inhibitors Tcf7l1 and Ctnnbip1. Our approach facilitates reconstructing spatial atlases of multiple cellular features in the liver and other structured tissues.

Quantitative modeling of transcription and translation of an all-E. coli cell-free system

Cell-free transcription-translation (TXTL) is expanding as a polyvalent experimental platform to engineer biological systems outside living organisms. As the number of TXTL applications and users is rapidly growing, some aspects of this technology could be better characterized to provide a broader description of its basic working mechanisms. In particular, developing simple quantitative biophysical models that grasp the different regimes of in vitro gene expression, using relevant kinetic constants and concentrations of molecular components, remains insufficiently examined. In this work, we present an ODE (Ordinary Differential Equation)-based model of the expression of a reporter gene in an all E. coli TXTL that we apply to a set of regulatory elements spanning several orders of magnitude in strengths, far beyond the T7 standard system used in most of the TXTL platforms. Several key biochemical constants are experimentally determined through fluorescence assays. The robustness of the model is tested against the experimental parameters, and limitations of TXTL resources are described. We establish quantitative references between the performance of E. coli and synthetic promoters and ribosome binding sites. The model and the data should be useful for the TXTL community interested either in gene network engineering or in biomanufacturing beyond the conventional platforms relying on phage transcription.

Proteome response of two natural strains of Saccharomyces cerevisiae with divergent lignocellulosic inhibitor stress tolerance

Strains of Saccharomyces cerevisiae with improved tolerance to plant hydrolysates are of utmost importance for the cost-competitive production of value-added chemicals and fuels. However, engineering strategies are constrained by a lack of understanding of the yeast response to complex inhibitor mixtures. Natural S. cerevisiae isolates display niche-specific phenotypic and metabolic diversity, encoded in their DNA, which has evolved to overcome external stresses, utilise available resources and ultimately thrive in their challenging environments. Industrial and laboratory strains, however, lack these adaptations due to domestication. Natural strains can serve as a valuable resource to mitigate engineering constraints by studying the molecular mechanisms involved in phenotypic variance and instruct future industrial strain improvement to lignocellulosic hydrolysates. We, therefore, investigated the proteomic changes between two natural S. cerevisiae isolates when exposed to a lignocellulosic inhibitor mixture. Comparative shotgun proteomics revealed that isolates respond by regulating a similar core set of proteins in response to inhibitor stress. Furthermore, superior tolerance was linked to NAD(P)/H and energy homeostasis, concurrent with inhibitor and reactive oxygen species detoxification processes. We present several candidate proteins within the redox homeostasis and energy management cellular processes as possible targets for future modification and study. Data are available via ProteomeXchange with identifier PXD010868.

Automated generation of bacterial resource allocation models

Resource Balance Analysis (RBA) is a computational method based on resource allocation, which performs accurate quantitative predictions of whole-cell states (i.e. growth rate, metabolic fluxes, abundances of molecular machines including enzymes) across growth conditions. We present an integrated workflow of RBA together with the Python package RBApy. RBApy builds bacterial RBA models from annotated genome-scale metabolic models by adding descriptions of cellular processes relevant for growth and maintenance. The package includes functions for model simulation and calibration and for interfacing to Escher maps and Proteomaps for visualization. We demonstrate that RBApy faithfully reproduces results obtained by a hand-curated and experimentally validated RBA model for Bacillus subtilis. We also present a calibrated RBA model of Escherichia coli generated from scratch, which obtained excellent fits to measured flux values and enzyme abundances. RBApy makes whole-cell modelling accessible for a wide range of bacterial wild-type and engineered strains, as illustrated with a CO₂-fixing Escherichia coli strain. AVAILABILITY: RBApy is available at /https://github.com/SysBioInra/RBApy, under the licence GNU GPL version 3, and runs on Linux, Mac and Windows distributions.

Exoproteome Heterogeneity among Closely Related Staphylococcus aureus t437 Isolates and Possible Implications for Virulence

Staphylococcus aureus with spa-type t437 has been identified as a predominant community-associated methicillin-resistant S. aureus clone from Asia, which is also encountered in Europe. Molecular typing has previously shown that t437 isolates are highly similar regardless of geographical regions or host environments. The present study was aimed at assessing to what extent this high similarity is actually reflected in the production of secreted virulence factors. We therefore profiled the extracellular proteome, representing the main reservoir of virulence factors, of 20 representative clinical isolates by mass spectrometry. The results show that these isolates can be divided into three groups and nine subgroups based on exoproteome abundance signatures. This implies that S. aureus t437 isolates show substantial exoproteome heterogeneity. Nonetheless, 30 highly conserved extracellular proteins, of which about 50% have a predicted role in pathogenesis, were dominantly identified. To approximate the virulence of the 20 investigated isolates, we employed infection models based on Galleria mellonella and HeLa cells. The results show that the grouping of clinical isolates based on their exoproteome profile can be related to virulence. We consider this outcome important as our approach provides a tool to pinpoint differences in virulence among seemingly highly similar clinical isolates of S. aureus.

Multi-omics insights into functional alterations of the liver in insulin-deficient diabetes mellitus

OBJECTIVE

The liver regulates the availability of insulin to other tissues and is the first line insulin response organ physiologically exposed to higher insulin concentrations than the periphery. Basal insulin during fasting inhibits hepatic gluconeogenesis and glycogenolysis, whereas postprandial insulin peaks stimulate glycogen synthesis. The molecular consequences of chronic insulin deficiency for the liver have not been studied systematically.

METHODS

We analyzed liver samples of a genetically diabetic pig model (MIDY) and of wild-type (WT) littermate controls by RNA sequencing, proteomics, and targeted metabolomics/lipidomics.

RESULTS

Cross-omics analyses revealed increased activities in amino acid metabolism, oxidation of fatty acids, ketogenesis, and gluconeogenesis in the MIDY samples. In particular, the concentrations of the ketogenic enzyme 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2) and of retinol dehydrogenase 16 (RDH16), which catalyzes the first step in retinoic acid biogenesis, were highly increased. Accordingly, elevated levels of retinoic acid, which stimulates the expression of the gluconeogenic enzyme phosphoenolpyruvate carboxykinase (PCK1), were measured in the MIDY samples. In contrast, pathways related to extracellular matrix and inflammation/pathogen defense response were less active than in the WT samples.

CONCLUSIONS

The first multi-omics study of a clinically relevant diabetic large animal model revealed molecular signatures and key drivers of functional alterations of the liver in insulin-deficient diabetes mellitus. The multi-omics data set provides a valuable resource for comparative analyses with other experimental or clinical data sets.

Virulence Factors Produced by Staphylococcus aureus Biofilms Have a Moonlighting Function Contributing to Biofilm Integrity

Staphylococcus aureus is the causative agent of various biofilm-associated infections in humans causing major healthcare problems worldwide. This type of infection is inherently difficult to treat because of a reduced metabolic activity of biofilm-embedded cells and the protective nature of a surrounding extracellular matrix (ECM). However, little is known about S. aureus biofilm physiology and the proteinaceous composition of the ECM. Thus, we cultivated S. aureus biofilms in a flow system and comprehensively profiled intracellular and extracellular (ECM and flow-through (FT)) biofilm proteomes, as well as the extracellular metabolome compared with planktonic cultures. Our analyses revealed the expression of many pathogenicity factors within S. aureus biofilms as indicated by a high abundance of capsule biosynthesis proteins along with various secreted virulence factors, including hemolysins, leukotoxins, and lipases as a part of the ECM. The activity of ECM virulence factors was confirmed in a hemolysis assay and a Galleria mellonella pathogenicity model. In addition, we uncovered a so far unacknowledged moonlighting function of secreted virulence factors and ribosomal proteins trapped in the ECM: namely their contribution to biofilm integrity. Mechanistically, it was revealed that this stabilizing effect is mediated by the strong positive charge of alkaline virulence factors and ribosomal proteins in an acidic ECM environment, which is caused by the release of fermentation products like formate, lactate, and acetate because of oxygen limitation in biofilms. The strong positive charge of these proteins most likely mediates electrostatic interactions with anionic cell surface components, eDNA, and anionic metabolites. In consequence, this leads to strong cell aggregation and biofilm stabilization. Collectively, our study identified a new molecular mechanism during S. aureus biofilm formation and thus significantly widens the understanding of biofilm-associated S. aureus infections - an essential prerequisite for the development of novel antimicrobial therapies.

Absolute Measurements of mRNA Translation in Caulobacter crescentus Reveal Important Fitness Costs of Vitamin B12 Scavenging

Caulobacter crescentus is a model system of the bacterial cell cycle culminating in asymmetric cell division, with each daughter cell inheriting a distinct set of proteins. While a genetic network of master transcription factors coordinates the cell cycle timing of transcription for nearly 20% of Caulobacter genes, we lack knowledge of how many of each protein “part” encoded in the genome are synthesized. Therefore, to determine the absolute production rates across the genome, we performed ribosome profiling, providing, for the first time, a quantitative resource with measurements of each protein “part” needed to generate daughter cells. This resource furthers the goal of a systems-level understanding of the genetic network controlling asymmetric cell division. To highlight the utility of this data set, we probe the protein synthesis cost of a B₁₂ utilization pathway and provide new insights into Caulobacter’s adaptation to its natural environments.

Caulobacter crescentus is a model for the bacterial cell cycle which culminates in asymmetric cell division, yet little is known about the absolute levels of protein synthesis of the cellular parts needed to complete the cell cycle. Here we utilize ribosome profiling to provide absolute measurements of mRNA translation in C. crescentus, providing an important resource with quantitative genome-wide measurements of protein output across individual genes. Analysis of protein synthesis rates revealed ∼4.5% of cellular protein synthesis is for genes related to vitamin B₁₂ import (btuB) and B₁₂-independent methionine biosynthesis (metE) when grown in common growth media lacking B₁₂. While its facultative B₁₂ lifestyle provides a fitness advantage in the absence of B₁₂, we find that it provides a fitness disadvantage of the cells in the presence of B₁₂, potentially explaining why many Caulobacter species have lost the metE gene and become obligates for B₁₂.

IMPORTANCECaulobacter crescentus is a model system of the bacterial cell cycle culminating in asymmetric cell division, with each daughter cell inheriting a distinct set of proteins. While a genetic network of master transcription factors coordinates the cell cycle timing of transcription for nearly 20% of Caulobacter genes, we lack knowledge of how many of each protein “part” encoded in the genome are synthesized. Therefore, to determine the absolute production rates across the genome, we performed ribosome profiling, providing, for the first time, a quantitative resource with measurements of each protein “part” needed to generate daughter cells. This resource furthers the goal of a systems-level understanding of the genetic network controlling asymmetric cell division. To highlight the utility of this data set, we probe the protein synthesis cost of a B₁₂ utilization pathway and provide new insights into Caulobacter’s adaptation to its natural environments.

Author Video: An author video summary of this article is available.

Characterization of the all-E. coli transcription-translation system myTXTL by mass spectrometry

RATIONALE

Cell-free transcription-translation (TXTL) is becoming a popular technology to prototype and engineer biological systems outside living organisms. TXTL relies commonly on a cytoplasmic extract that provides the molecular components necessary to recapitulate gene expression in vitro, where most of the available systems are derived from E. coli. The proteinic and enzymatic composition of lysates, however, is typically unknown. In this work, we analyzed by mass spectrometry the molecular constituents of the all-E. coli TXTL platform myTXTL prepared from the E. coli strain BL21 Rosetta2.

METHODS

Standard TXTL reactions were assembled and executed for 10-12 hours at 29°C. In addition to a no-DNA control, four DNA programs were executed in separate reactions to synthesize the reporter protein deGFP as well as the phages MS2, phix174 and T7. The reactions were treated according to standard procedures (trypsin treatment, cleaning) before performing liquid chromatography/mass spectrometry (LC/MS). Data analysis was performed using Sequest and protein identification using Scaffold.

RESULTS

A total of 500-800 proteins were identified by LC/MS in the blank reactions. We organized the most abundant protein sets into several categories pertaining, in particular, to transcription, translation and ATP regeneration. The synthesis of deGFP was easily measured. The major structural proteins that compose the three phages MS2, phix174 and T7 were also identified.

CONCLUSIONS

Mass spectrometry is a practical tool to characterize biochemical solutions as complex as a cell-free TXTL reaction and to determine the presence of synthesized proteins. The data presented demonstrate that the composition of TXTL based on lysates can be used to validate some underlying molecular mechanisms implicated in cell-free protein synthesis. The composition of the lysate shows significant differences with respect to similar studies on other E. coli strains.

The Cell and the Sum of Its Parts: Patterns of Complexity in Biosignatures as Revealed by Deep UV Raman Spectroscopy

The next NASA-led Mars mission (Mars 2020) will carry a suite of instrumentation dedicated to investigating Martian history and the in situ detection of potential biosignatures. SHERLOC, a deep UV Raman/Fluorescence spectrometer has the ability to detect and map the distribution of many organic compounds, including the aromatic molecules that are fundamental building blocks of life on Earth, at concentrations down to 1 ppm. The mere presence of organic compounds is not a biosignature: there is widespread distribution of reduced organic molecules in the Solar System. Life utilizes a select few of these molecules creating conspicuous enrichments of specific molecules that deviate from the distribution expected from purely abiotic processes. The detection of far from equilibrium concentrations of a specific subset of organic molecules, such as those uniquely enriched by biological processes, would comprise a universal biosignature independent of specific terrestrial biochemistry. The detectability and suitability of a small subset of organic molecules to adequately describe a living system is explored using the bacterium Escherichia coli as a model organism. The DUV Raman spectra of E. coli cells are dominated by the vibrational modes of the nucleobases adenine, guanine, cytosine, and thymine, and the aromatic amino acids tyrosine, tryptophan, and phenylalanine. We demonstrate that not only does the deep ultraviolet (DUV) Raman spectrum of E. coli reflect a distinct concentration of specific organic molecules, but that a sufficient molecular complexity is required to deconvolute the cellular spectrum. Furthermore, a linear combination of the DUV resonant compounds is insufficient to fully describe the cellular spectrum. The residual in the cellular spectrum indicates that DUV Raman spectroscopy enables differentiating between the presence of biomolecules and the complex uniquely biological organization and arrangements of these molecules in living systems. This study demonstrates the ability of DUV Raman spectroscopy to interrogate a complex biological system represented in a living cell, and differentiate between organic detection and a series of Raman features that derive from the molecular complexity inherent to life constituting a biosignature.

Evaluation of meter-long monolithic columns for selected reaction monitoring mass spectrometry

Proteome is extremely complex as many proteins with a large dynamic range are involved. Nano-liquid chromatography/mass spectrometry-based proteomics has made it possible to separate and identify thousands of proteins in one shot. Although the number of identified proteins in proteomics has significantly improved, it is necessary to increase detection sensitivity to clearly identify low-abundant proteins. In this study, we developed meter-long monolithic columns with a small inner diameter and applied them to selected reaction monitoring-based proteomics for improving proteomic detection sensitivity. Bovine serum albumin tryptic digests were analyzed with optimized selected reaction monitoring methods, and separation efficiency and detection sensitivity in each monolithic column were evaluated. As a result, peak capacity increased by about 1.8-fold and peak area of peptide levels increased by about 2.3-fold. Although flow rate was reduced during analysis with columns of a smaller inner diameter, the peak area reproducibility was maintained. These data displayed the value of meter-long monolithic columns with small inner diameter for selected reaction monitoring-based proteomics.

Investigating Lactococcus lactis MG1363 Response to Phage p2 Infection at the Proteome Level

Phages are viruses that specifically infect and eventually kill their bacterial hosts. Bacterial fermentation and biotechnology industries see them as enemies, however, they are also investigated as antibacterial agents for the treatment or prevention of bacterial infections in various sectors. They also play key ecological roles in all ecosystems. Despite decades of research some aspects of phage biology are still poorly understood. In this study, we used label-free quantitative proteomics to reveal the proteotypes of Lactococcus lactis MG1363 during infection by the virulent phage p2, a model for studying the biology of phages infecting Gram-positive bacteria. Our approach resulted in the high-confidence detection and quantification of 59% of the theoretical bacterial proteome, including 226 bacterial proteins detected only during phage infection and 6 proteins unique to uninfected bacteria. We also identified many bacterial proteins of differing abundance during the infection. Using this high-throughput proteomic datasets, we selected specific bacterial genes for inactivation using CRISPR-Cas9 to investigate their involvement in phage replication. One knockout mutant lacking gene llmg_0219 showed resistance to phage p2 because of a deficiency in phage adsorption. Furthermore, we detected and quantified 78% of the theoretical phage proteome and identified many proteins of phage p2 that had not been previously detected. Among others, we uncovered a conserved small phage protein (pORFN1) coded by an unannotated gene. We also applied a targeted approach to achieve greater sensitivity and identify undetected phage proteins that were expected to be present. This allowed us to follow the fate of pORF46, a small phage protein of low abundance. In summary, this work offers a unique view of the virulent phages' takeover of bacterial cells and provides novel information on phage-host interactions.

Selection of a Real-Time PCR Housekeeping Gene Panel in Human Endothelial Colony Forming Cells for Cellular Senescence Studies

Endothelial Colony Forming Cells (ECFCs) represent a subset of endothelial progenitors with well-documented vasoreparative capacity. However, cellular senescence, which occurs due to aging, diabetes, smoking, or tissue inflammation, renders these cells dysfunctional. Therefore, there is growing interest in studying expression of senescence markers in ECFCs. RT-qPCR is the most commonly used technique to quantify gene expression and the proper choice of reference genes used for data normalization is critical for accurate quantification. It has been reported that the expression of commonly used housekeeping genes is often unstable in senescence. To identify the most suitable reference genes for ECFC senescence studies, we analyzed a microarray dataset, which compared the gene expression between proliferating and senescent ECFCs. In addition to replicative senescence, the data included X-ray-induced and Etoposide-induced senescence. We used the geNorm algorithm to identify the most stable genes across all studied conditions. Gene Ontology analysis found that the most stable genes belonged to the KEGG category of Genetic Information Processing. The optimal combination of housekeeping genes for ECFC senescence was found to include four ribosomal protein genes; RPL13, RPL31, RPL37, and RPL30. The RT-qPCR validation confirmed that normalization with our novel panel was more sensitive in identifying senescence markers compared to commonly used genes such as ACTB, UBC, and GAPDH.

A transcriptome-wide analysis deciphers distinct roles of G1 cyclins in temporal organization of the yeast cell cycle

Oscillating gene expression is crucial for correct timing and progression through cell cycle. In Saccharomyces cerevisiae, G1 cyclins Cln1-3 are essential drivers of the cell cycle and have an important role for temporal fine-tuning. We measured time-resolved transcriptome-wide gene expression for wild type and cyclin single and double knockouts over cell cycle with and without osmotic stress. Clustering of expression profiles, peak time detection of oscillating genes, integration with transcription factor network dynamics, and assignment to cell cycle phases allowed us to quantify the effect of genetic or stress perturbations on the duration of cell cycle phases. Cln1 and Cln2 showed functional differences, especially affecting later phases. Deletion of Cln3 led to a delay of START followed by normal progression through later phases. Our data and network analysis suggest mutual effects of cyclins with the transcriptional regulators SBF and MBF.

Chlorophyll catabolism precedes changes in chloroplast structure and proteome during leaf senescence

The earliest visual changes of leaf senescence occur in the chloroplast as chlorophyll is degraded and photosynthesis declines. Yet, a comprehensive understanding of the sequence of catabolic events occurring in chloroplasts during natural leaf senescence is still missing. Here, we combined confocal and electron microscopy together with proteomics and biochemistry to follow structural and molecular changes during Arabidopsis leaf senescence. We observed that initiation of chlorophyll catabolism precedes other breakdown processes. Chloroplast size, stacking of thylakoids, and efficiency of PSII remain stable until late stages of senescence, whereas the number and size of plastoglobules increase. Unlike catabolic enzymes, whose level increase, the level of most proteins decreases during senescence, and chloroplast proteins are overrepresented among these. However, the rate of their disappearance is variable, mostly uncoordinated and independent of their inherent stability during earlier developmental stages. Unexpectedly, degradation of chlorophyll-binding proteins lags behind chlorophyll catabolism. Autophagy and vacuole proteins are retained at relatively high levels, highlighting the role of extra-plastidic degradation processes especially in late stages of senescence. The observation that chlorophyll catabolism precedes all other catabolic events may suggest that this process enables or signals further catabolic processes in chloroplasts.