Integrative analysis of transcriptomic and proteomic data: challenges, solutions and applications

Proteomic features of gray matter layers and superficial white matter of the rhesus monkey neocortex: comparison of prefrontal area 46 and occipital area 17

In this novel large-scale multiplexed immunofluorescence study we comprehensively characterized and compared layer-specific proteomic features within regions of interest of the widely divergent dorsolateral prefrontal cortex (A46) and primary visual cortex (A17) of adult rhesus monkeys. Twenty-eight markers were imaged in rounds of sequential staining, and their spatial distribution precisely quantified within gray matter layers and superficial white matter. Cells were classified as neurons, astrocytes, oligodendrocytes, microglia, or endothelial cells. The distribution of fibers and blood vessels were assessed by quantification of staining intensity across regions of interest. This method revealed multivariate similarities and differences between layers and areas. Protein expression in neurons was the strongest determinant of both laminar and regional differences, whereas protein expression in glia was more important for intra-areal laminar distinctions. Among specific results, we observed a lower glia-to-neuron ratio in A17 than in A46 and the pan-neuronal markers HuD and NeuN were differentially distributed in both brain areas with a lower intensity of NeuN in layers 4 and 5 of A17 compared to A46 and other A17 layers. Astrocytes and oligodendrocytes exhibited distinct marker-specific laminar distributions that differed between regions; notably, there was a high proportion of ALDH1L1-expressing astrocytes and of oligodendrocyte markers in layer 4 of A17. The many nuanced differences in protein expression between layers and regions observed here highlight the need for direct assessment of proteins, in addition to RNA expression, and set the stage for future protein-focused studies of these and other brain regions in normal and pathological conditions.

Molecular and functional profiling of cell diversity and identity in the lateral superior olive, an auditory brainstem center with ascending and descending projections

The lateral superior olive (LSO), a prominent integration center in the auditory brainstem, contains a remarkably heterogeneous population of neurons. Ascending neurons, predominantly principal neurons (pLSOs), process interaural level differences for sound localization. Descending neurons (lateral olivocochlear neurons, LOCs) provide feedback into the cochlea and are thought to protect against acoustic overload. The molecular determinants of the neuronal diversity in the LSO are largely unknown. Here, we used patch-seq analysis in mice at postnatal days P10-12 to classify developing LSO neurons according to their functional and molecular profiles. Across the entire sample (n = 86 neurons), genes involved in ATP synthesis were particularly highly expressed, confirming the energy expenditure of auditory neurons. Two clusters were identified, pLSOs and LOCs. They were distinguished by 353 differentially expressed genes (DEGs), most of which were novel for the LSO. Electrophysiological analysis confirmed the transcriptomic clustering. We focused on genes affecting neuronal input-output properties and validated some of them by immunohistochemistry, electrophysiology, and pharmacology. These genes encode proteins such as osteopontin, Kv11.3, and Kvβ3 (pLSO-specific), calcitonin-gene-related peptide (LOC-specific), or Kv7.2 and Kv7.3 (no DEGs). We identified 12 "Super DEGs" and 12 genes showing "Cluster similarity." Collectively, we provide fundamental and comprehensive insights into the molecular composition of individual ascending and descending neurons in the juvenile auditory brainstem and how this may relate to their specific functions, including developmental aspects.

Integrative multi-omics analyses of date palm (Phoenix dactylifera) roots and leaves reveal how the halophyte land plant copes with sea water

Date palm (Phoenix dactylifera L.) is able to grow and complete its life cycle while being rooted in highly saline soils. Which of the many well-known salt-tolerance strategies are combined to fine-tune this remarkable resilience is unknown. The precise location, whether in the shoot or the root, where these strategies are employed remains uncertain, leaving us unaware of how the various known salt-tolerance mechanisms are integrated to fine-tune this remarkable resilience. To address this shortcoming, we exposed date palm to a salt stress dose equivalent to seawater for up to 4 weeks and applied integrative multi-omics analyses followed by targeted metabolomics, hormone, and ion analyses. Integration of proteomic into transcriptomic data allowed a view beyond simple correlation, revealing a remarkably high degree of convergence between gene expression and protein abundance. This sheds a clear light on the acclimatization mechanisms employed, which depend on reprogramming of protein biosynthesis. For growth in highly saline habitats, date palm effectively combines various salt-tolerance mechanisms found in both halophytes and glycophytes: "avoidance" by efficient sodium and chloride exclusion at the roots, and "acclimation" by osmotic adjustment, reactive oxygen species scavenging in leaves, and remodeling of the ribosome-associated proteome in salt-exposed root cells. Combined efficiently as in P. dactylifera L., these sets of mechanisms seem to explain the palm's excellent salt stress tolerance.

Exploiting DNA methylation in cassava under water deficit for crop improvement

DNA methylation plays a key role in the development and plant responses to biotic and abiotic stresses. This work aimed to evaluate the DNA methylation in contrasting cassava genotypes for water deficit tolerance. The varieties BRS Formosa (bitter) and BRS Dourada (sweet) were grown under greenhouse conditions for 50 days, and afterwards, irrigation was suspended. The stressed (water deficit) and non-stressed plants (negative control) consisted the treatments with five plants per variety. The DNA samples of each variety and treatment provided 12 MethylRAD-Seq libraries (two cassava varieties, two treatments, and three replicates). The sequenced data revealed methylated sites covering 18 to 21% of the Manihot esculenta Crantz genome, depending on the variety and the treatment. The CCGG methylated sites mapped mostly in intergenic regions, exons, and introns, while the CCNGG sites mapped mostly intergenic, upstream, introns, and exons regions. In both cases, methylated sites in UTRs were less detected. The differentially methylated sites analysis indicated distinct methylation profiles since only 12% of the sites (CCGG and CCNGG) were methylated in both varieties. Enriched gene ontology terms highlighted the immediate response of the bitter variety to stress, while the sweet variety appears to suffer more potential stress-damages. The predicted protein-protein interaction networks reinforced such profiles. Additionally, the genomes of the BRS varieties uncovered SNPs/INDELs events covering genes stood out by the interactomes. Our data can be useful in deciphering the roles of DNA methylation in cassava drought-tolerance responses and adaptation to abiotic stresses.

Estrogen-Related Receptor Agonism Reverses Mitochondrial Dysfunction and Inflammation in the Aging Kidney

A gradual decline in renal function occurs even in healthy aging individuals. In addition to aging, per se, concurrent metabolic syndrome and hypertension, which are common in the aging population, can induce mitochondrial dysfunction and inflammation, which collectively contribute to age-related kidney dysfunction and disease. This study examined the role of the nuclear hormone receptors, the estrogen-related receptors (ERRs), in regulation of age-related mitochondrial dysfunction and inflammation. The ERRs were decreased in both aging human and mouse kidneys and were preserved in aging mice with lifelong caloric restriction (CR). A pan-ERR agonist, SLU-PP-332, was used to treat 21-month-old mice for 8 weeks. In addition, 21-month-old mice were treated with a stimulator of interferon genes (STING) inhibitor, C-176, for 3 weeks. Remarkably, similar to CR, an 8-week treatment with a pan-ERR agonist reversed the age-related increases in albuminuria, podocyte loss, mitochondrial dysfunction, and inflammatory cytokines, via the cyclic GMP-AMP synthase-STING and STAT3 signaling pathways. A 3-week treatment of 21-month-old mice with a STING inhibitor reversed the increases in inflammatory cytokines and the senescence marker, p21/cyclin dependent kinase inhibitor 1A (Cdkn1a), but also unexpectedly reversed the age-related decreases in PPARG coactivator (PGC)-1α, ERRα, mitochondrial complexes, and medium chain acyl coenzyme A dehydrogenase (MCAD) expression. These studies identified ERRs as CR mimetics and as important modulators of age-related mitochondrial dysfunction and inflammation. These findings highlight novel druggable pathways that can be further evaluated to prevent progression of age-related kidney disease.

Dynamic RNA profiles in the small intestinal epithelia of cats after Toxoplasma gondii infection

BACKGROUND

Felids are the only definitive hosts of Toxoplasma gondii. However, the biological features of the feline small intestine following T. gondii infection are poorly understood. We investigated the changes in the expression of RNAs (including mRNAs, long non-coding RNAs and circular RNAs) in the small intestinal epithelia of cats following T. gondii infection to improve our understanding of the life cycle of T. gondii and cat responses to T. gondii infection.

METHODS

Fifteen cats were randomly assigned to five groups, and the infection groups were inoculated with 600 tissue cysts of the T. gondii Pru strain by gavage. The small intestinal epithelia of cats were collected at 6, 10, 14, and 30 days post infection (DPI). Using high-throughput RNA sequencing (RNA-seq), we investigated the changes in RNA expression. The expression levels of differentially expressed (DE) genes and non-coding RNAs (ncRNAs) identified by RNA-seq were validated by quantitative reverse transcription PCR (qRT-PCR). Differential expression was determined using the DESeq R package.

RESULTS

In total, 207 annotated lncRNAs, 20,552 novel lncRNAs, 3342 novel circRNAs and 19,409 mRNAs were identified. Among these, 70 to 344 DE mRNAs, lncRNAs and circRNAs were detected, and the post-cleavage binding sites between 725 ncRNAs and 2082 miRNAs were predicted. Using the co-location method, we predicted that a total of 235 lncRNAs target 1044 protein-coding genes, while the results of co-expression analysis revealed that 174 lncRNAs target 2097 mRNAs. Pathway enrichment analyses of the genes targeted by ncRNAs suggested that most ncRNAs were significantly enriched in immune or diseases-related pathways. NcRNA regulatory networks revealed that a single ncRNA could be directly or indirectly regulated by multiple genes or ncRNAs that could influence the immune response of cats. Co-expression analysis showed that 242 circRNAs, mainly involved in immune responses, were significantly associated with T. gondii infection. In contrast, 1352 protein coding RNAs, mainly involved in nucleic acid process/repair pathways or oocyte development pathways, were negatively associated with T. gondii infection.

CONCLUSIONS

This study is the first to reveal the expression profiles of circRNAs, lncRNAs and mRNAs in the cat small intestine following T. gondii infection and will facilitate the elucidation of the role of ncRNAs in the pathogenesis of T. gondii infection in its definitive host, thereby facilitating the development of novel intervention strategies against T. gondii infection in humans and animals.

Quantitative proteomic profiling identifies global protein network dynamics in murine embryonic heart development

Defining the mechanisms that govern heart development is essential for identifying the etiology of congenital heart disease. Here, quantitative proteomics was used to measure temporal changes in the proteome at critical stages of murine embryonic heart development. Global temporal profiles of the over 7,300 proteins uncovered signature cardiac protein interaction networks that linked protein dynamics with molecular pathways. Using this integrated dataset, we identified and demonstrated a functional role for the mevalonate pathway in regulating the cell cycle of embryonic cardiomyocytes. Overall, our proteomic datasets are a resource for studying events that regulate embryonic heart development and contribute to congenital heart disease.

Transcriptomic and proteomic profiling of the anterior cingulate cortex in neuropathic pain model rats

Background

Neuropathic pain (NP) takes a heavy toll on individual life quality, yet gaps in its molecular characterization persist and effective therapy is lacking. This study aimed to provide comprehensive knowledge by combining transcriptomic and proteomic data of molecular correlates of NP in the anterior cingulate cortex (ACC), a cortical hub responsible for affective pain processing.

Methods

The NP model was established by spared nerve injury (SNI) in Sprague-Dawley rats. RNA sequencing and proteomic data from the ACC tissue isolated from sham and SNI rats 2 weeks after surgery were integrated to compare their gene and protein expression profiles. Bioinformatic analyses were performed to figure out the functions and signaling pathways of the differentially expressed genes (DEGs) and differentially expressed proteins (DEPs) enriched in.

Results

Transcriptomic analysis identified a total of 788 DEGs (with 49 genes upregulated) after SNI surgery, while proteomic analysis found 222 DEPs (with 89 proteins upregulated). While Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of the DEGs suggested that most of the altered genes were involved in synaptic transmission and plasticity, bioinformatics analysis of the DEPs revealed novel critical pathways associated with autophagy, mitophagy, and peroxisome. Notably, we noticed functionally important NP-related changes in the protein that occurred in the absence of corresponding changes at the level of transcription. Venn diagram analysis of the transcriptomic and proteomic data identified 10 overlapping targets, among which only three genes (XK-related protein 4, NIPA-like domain-containing 3, and homeodomain-interacting protein kinase 3) showed concordance in the directions of change and strong correlations between mRNA and protein levels.

Conclusion

The present study identified novel pathways in the ACC in addition to confirming previously reported mechanisms for NP etiology, and provided novel mechanistic insights for future research on NP treatment. These findings also imply that mRNA profiling alone fails to provide a complete landscape of molecular pain in the ACC. Therefore, explorations of changes at the level of protein are necessary to understand NP processes that are not transcriptionally modulated.

Marked inter-strain heterogeneity in the differential expression of some key stress response and virulence-related genes between planktonic and biofilm cells in Listeria monocytogenes

Listeria monocytogenes is a facultatively intracellular pathogenic bacterium that can provoke invasive listeriosis, a severe foodborne infection in humans. Outside the host, this is capable to survive for long periods in soil, and water, as well as on plants, while, like many other microorganisms, this can also attach to abiotic surfaces, such as food contact ones, forming biofilms on them. It has been suggested that inside those sessile communities, L. monocytogenes cells not only display an increased stress tolerance but may also boost their pathogenicity. In this work, the expression of ten key stress response and/or virulence-related genes (i.e., groEL, hly, iap, inlA, inlB, lisK, mdrD, mdrL, prfA, and sigB) was studied in three different L. monocytogenes strains (AAL20066, AAL20107, and PL24), all isolated from foods and each belonging to a different listeriosis-associated serovar (1/2a, 1/2b, and 1/2c, respectively). For this, each strain was initially left to develop a mature biofilm on a model polystyrene surface (Petri dish) by incubating for 144 h (6 days) at 20 °C in tryptone soya broth (with medium renewal every 48 h). Following incubation, both biofilm and the surrounding free-swimming (planktonic) cells were recovered, and their gene expressions were comparatively evaluated through targeted reverse transcription-quantitative polymerase chain reactions (RT-qPCR). Results revealed a strain-dependent differential gene expression between the two cell types. Thus, for instance, in strain AAL20107 (ser. 1/2b) biofilm growth worryingly resulted in a significant overexpression of all the studied genes (P < 0.05), whereas in strain PL24 (ser. 1/2c), the expression of most genes (8/10) did not change upon biofilm growth, with only two of them (groEL and hly) being again significantly upregulated. Such transcriptomic strain variability in stress adaptation and/or virulence induction should be generally considered in the physiological studies of pathogenic biofilms and preferably upon designing and implementing novel and more efficient eradication methods.

Statistical and Computational Methods for Proteogenomic Data Analysis

Proteins are the functional molecules for almost all cellular and biological processes. They are also the targets of most drugs. Proteins employ complex, multilevel regulations, so their abundance levels do not well correlated with their mRNA expression levels. The structure, activity, and functional roles of proteins are affected by posttranslational modifications (PTM), which are even less correlated with mRNA expression levels than protein abundances. Comprehensive characterization of the proteomics data is critical for understanding the molecular and cellular mechanisms of biological systems and developing news therapeutics. Current large-scale proteomic profiling technologies, such as mass spectrometry, provide relative identification of peptides and proteins, with data vulnerable to outliers, batch effects, and nonrandom missingness. In order to perform high-quality proteomic data analysis, we will first introduce a data preprocessing and quality control pipeline that includes normalization, outlier detection and removal, batch effect identification and handling, and missing data imputation. Then, we will describe several statistical methods that leverage well-processed proteomic data to generate scientific discoveries, especially with an integration with genomics and transcriptomics. These methods cover topics like association analysis, network construction, clustering, and cell-type deconvolution. To demonstrate these methods, we will use the proteogenomic data from the lung squamous cell carcinoma study of the Clinical Proteomic Tumor Analysis Consortium and provide sample codes for data access and analyses.

Cross-feeding between cyanobacterium Synechococcus and Escherichia coli in an artificial autotrophic–heterotrophic coculture system revealed by integrated omics analysis

Background

Light-driven consortia, which consist of sucrose-secreting cyanobacteria and heterotrophic species, have attracted considerable attention due to their capability for the sustainable production of valuable chemicals directly from CO₂. In a previous study, we achieved a one-step conversion of sucrose secreted from cyanobacteria to fine chemicals by constructing an artificial coculture system consisting of sucrose-secreting Synechococcus elongateus cscB⁺ and 3-hydroxypropionic acid (3-HP) producing Escherichia coli ABKm. Analyses of the coculture system showed that the cyanobacterial cells grew better than their corresponding axenic cultures. To explore the underlying mechanism and to identify the metabolic nodes with the potential to further improve the coculture system, we conducted integrated transcriptomic, proteomic and metabolomic analyses.

Results

We first explored how the relieved oxidative stress affected cyanobacterial cell growth in a coculture system by supplementing additional ascorbic acid to CoBG-11 medium. We found that the cell growth of cyanobacteria was clearly improved with an additional 1 mM ascorbic acid under axenic culture; however, its growth was still slower than that in the coculture system, suggesting that the improved growth of Synechococcus cscB⁺ may be caused by multiple factors, including reduced oxidative stress. To further explore the cellular responses of cyanobacteria in the system, quantitative transcriptomics, proteomics and metabolomics were applied to Synechococcus cscB⁺. Analyses of differentially regulated genes/proteins and the abundance change of metabolites in the photosystems revealed that the photosynthesis of the cocultured Synechococcus cscB⁺ was enhanced. The decreased expression of the CO₂ transporter suggested that the heterotrophic partner in the system might supplement additional CO₂ to support the cell growth of Synechococcus cscB⁺. In addition, the differentially regulated genes and proteins involved in the nitrogen and phosphate assimilation pathways suggested that the supply of phosphate and nitrogen in the Co-BG11 medium might be insufficient.

Conclusion

An artificial coculture system capable of converting CO₂ to fine chemicals was established and then analysed by integrated omics analysis, which demonstrated that in the coculture system, the relieved oxidative stress and increased CO₂ availability improved the cell growth of cyanobacteria. In addition, the results also showed that the supply of phosphate and nitrogen in the Co-BG11 medium might be insufficient, which paves a new path towards the optimization of the coculture system in the future. Taken together, these results from the multiple omics analyses provide strong evidence that beneficial interactions can be achieved from cross-feeding and competition between phototrophs and prokaryotic heterotrophs and new guidelines for engineering more intelligent artificial consortia in the future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13068-022-02163-5.

Mapping secretome-mediated interaction between paired neuron–macrophage single cells

Neuron-immune interaction through secreted factors contributes significantly to the complex microenvironment in the central nervous system that could alter cell functionalities and fates in both physiological and pathological conditions, which remains poorly characterized at the single-cell level. Herein, using a spatially patterned antibody barcode microchip, we realized the mapping of 12 different secretomes, covering cytokines, neurotrophic factors (NFs), and neuron-derived exosomes (NDEs) from high-throughput, paired single cells (≥ 600) simultaneously under normal conditions and an Alzheimer’s disease (AD) model induced with amyloid beta protein 1-42 (Aβ 1–42 ). We applied the platform to analyze the secretion profiles from paired neuron–macrophage and neuron–microglia single cells with human cell lines. We found that pairwise neuron–macrophage interaction would trigger immune responses and attenuate neuron cells’ secretion, while neuron–microglia interaction generally results in opposite outcomes in secretion. When neuron cells are induced with Aβ 1–42 protein into the AD model, both neuron–macrophage and neuron–microglia interactions lead to increased cytokines and NDEs and decreased NFs. Further analysis of AD patients’ serum showed that NDEs were significantly higher in patients’ samples than in the control group, validating our observation from the interaction assay. Furthermore, we resolved previously undifferentiated heterogeneity underlying the secretions from single-neuron cells. We found that the NDE and NF secretion was less dependent on the paracrine signaling between one another and that secretions from neuron cells would attenuate after differentiation with Aβ 1–42 . This study demonstrates the mapping of the different secretomes from paired neuron-immune single cells, providing avenues for understanding how neurons and immune cells interact through the complex secretome network.

Transcriptomic and proteomic analysis of Staphylococcus aureus response to cuminaldehyde stress

The previous study indicated that cuminaldehyde (CUM) could be used as an antibacterial agent in sauced beef to reduce the propagation of Staphylococcus aureus (S. aureus). This research took sauced beef treated with 0.4 μL/mL CUM as the research object. Transcriptomic and proteomic methods were used to comprehensively analyze the changes in genes and proteins of S. aureus under CUM stress. A total of 258 differentially expressed genes (DEGs, 178 up-regulated and 80 down-regulated) and 384 differentially expressed proteins (DEPs, 61 up-regulated and 323 down-regulated) were found. It was observed that CUM destroyed the cell wall and cell membrane by inhibiting the synthesis of peptidoglycan and fatty acid. Low energy consumption strategies were formed by reducing glycolysis and ribosome de novo synthesis. The levels of genes and proteins associated with the glycine, serine, threonine, methionine, cysteine, and branched-chain amino acids were dramatically changed, which impaired protein synthesis and reduced bacterial viability. In addition, the up-regulated DEGs and DEFs involved in DNA replication, recombination and single-stranded DNA-binding contributed to DNA repair. Moreover, ATP-binding cassettes (ABC) transporters were also perturbed, such as the uptake of betaine and iron were inhibited. Thus, this study revealed the response mechanism of S. aureus under the stress of CUM, and provided a theoretical basis for the application of CUM in meat products.

Coral holobiont cues prime Endozoicomonas for a symbiotic lifestyle

Endozoicomonas are prevalent, abundant bacterial associates of marine animals, including corals. Their role in holobiont health and functioning, however, remains poorly understood. To identify potential interactions within the coral holobiont, we characterized the novel isolate Endozoicomonas marisrubri sp. nov. 6c and assessed its transcriptomic and proteomic response to tissue extracts of its native host, the Red Sea coral Acropora humilis. We show that coral tissue extracts stimulated differential expression of genes putatively involved in symbiosis establishment via the modulation of the host immune response by E. marisrubri 6c, such as genes for flagellar assembly, ankyrins, ephrins, and serpins. Proteome analyses revealed that E. marisrubri 6c upregulated vitamin B1 and B6 biosynthesis and glycolytic processes in response to holobiont cues. Our results suggest that the priming of Endozoicomonas for a symbiotic lifestyle involves the modulation of host immunity and the exchange of essential metabolites with other holobiont members. Consequently, Endozoicomonas may play an important role in holobiont nutrient cycling and may therefore contribute to coral health, acclimatization, and adaptation.

Effects of Psychotropic Drugs on Ribosomal Genes and Protein Synthesis

Altered protein synthesis has been implicated in the pathophysiology of several neuropsychiatric disorders, particularly schizophrenia. Ribosomes are the machinery responsible for protein synthesis. However, there remains little information on whether current psychotropic drugs affect ribosomes and contribute to their therapeutic effects. We treated human neuronal-like (NT2-N) cells with amisulpride (10 µM), aripiprazole (0.1 µM), clozapine (10 µM), lamotrigine (50 µM), lithium (2.5 mM), quetiapine (50 µM), risperidone (0.1 µM), valproate (0.5 mM) or vehicle control for 24 h. Transcriptomic and gene set enrichment analysis (GSEA) identified that the ribosomal pathway was altered by these drugs. We found that three of the eight drugs tested significantly decreased ribosomal gene expression, whilst one increased it. Most changes were observed in the components of cytosolic ribosomes and not mitochondrial ribosomes. Protein synthesis assays revealed that aripiprazole, clozapine and lithium all decreased protein synthesis. Several currently prescribed psychotropic drugs seem to impact ribosomal gene expression and protein synthesis. This suggests the possibility of using protein synthesis inhibitors as novel therapeutic agents for neuropsychiatric disorders.

Integrated Multilayer Omics Reveals the Genomic, Proteomic, and Metabolic Influences of Histidyl Dipeptides on the Heart

Background

Histidyl dipeptides such as carnosine are present in a micromolar to millimolar range in mammalian hearts. These dipeptides facilitate glycolysis by proton buffering. They form conjugates with reactive aldehydes, such as acrolein, and attenuate myocardial ischemia–reperfusion injury. Although these dipeptides exhibit multifunctional properties, a composite understanding of their role in the myocardium is lacking.

Methods and Results

To identify histidyl dipeptide–mediated responses in the heart, we used an integrated triomics approach, which involved genome‐wide RNA sequencing, global proteomics, and unbiased metabolomics to identify the effects of cardiospecific transgenic overexpression of the carnosine synthesizing enzyme, carnosine synthase (Carns), in mice. Our result showed that higher myocardial levels of histidyl dipeptides were associated with extensive changes in the levels of several microRNAs, which target the expression of contractile proteins, β‐fatty acid oxidation, and citric acid cycle (TCA) enzymes. Global proteomic analysis showed enrichment in the expression of contractile proteins, enzymes of β‐fatty acid oxidation, and the TCA in the Carns transgenic heart. Under aerobic conditions, the Carns transgenic hearts had lower levels of short‐ and long‐chain fatty acids as well as the TCA intermediate—succinic acid; whereas, under ischemic conditions, the accumulation of fatty acids and TCA intermediates was significantly attenuated. Integration of multiple data sets suggested that β‐fatty acid oxidation and TCA pathways exhibit correlative changes in the Carns transgenic hearts at all 3 levels.

Conclusions

Taken together, these findings reveal a central role of histidyl dipeptides in coordinated regulation of myocardial structure, function, and energetics.

Low complexity regions in mammalian proteins are associated with low protein abundance and high transcript abundance

Low Complexity Regions (LCRs) are present in a surprisingly large number of eukaryotic proteins. These highly repetitive and compositionally biased sequences are often structurally disordered, bind promiscuously, and evolve rapidly. Frequently studied in terms of evolutionary dynamics, little is known about how LCRs affect the expression of the proteins which contain them. It would be expected that rapidly evolving LCRs are unlikely to be tolerated in strongly conserved, highly abundant proteins, leading to lower overall abundance in proteins which contain LCRs. To test this hypothesis and examine the associations of protein abundance and transcript abundance with the presence of LCRs, we have integrated high-throughput data from across mammals. We have found that LCRs are indeed associated with reduced protein abundance, but are also associated with elevated transcript abundance. These associations are qualitatively consistent across 12 human tissues and nine mammalian species. The differential impacts of LCRs on abundance at the protein and transcript level are not explained by differences in either protein degradation rates or the inefficiency of translation for LCR containing proteins. We suggest that rapidly evolving LCRs are a source of selective pressure on the regulatory mechanisms which maintain steady-state protein abundance levels.

Epigenomics as a paradigm to understand the nuances of phenotypes

Quantifying the relative importance of genomic and epigenomic modulators of phenotype is a focal challenge in comparative physiology, but progress is constrained by availability of data and analytic methods. Previous studies have linked physiological features to coding DNA sequence, regulatory DNA sequence, and epigenetic state, but few have disentangled their relative contributions or unambiguously distinguished causative effects ('drivers') from correlations. Progress has been limited by several factors, including the classical approach of treating continuous and fluid phenotypes as discrete and static across time and environment, and difficulty in considering the full diversity of mechanisms that can modulate phenotype, such as gene accessibility, transcription, mRNA processing and translation. We argue that attention to phenotype nuance, progressing to association with epigenetic marks and then causal analyses of the epigenetic mechanism, will enable clearer evaluation of the evolutionary path. This would underlie an essential paradigm shift, and power the search for links between genomic and epigenomic features and physiology. Here, we review the growing knowledge base of gene-regulatory mechanisms and describe their links to phenotype, proposing strategies to address widely recognized challenges.

Proteomic quantitative study of dorsal root ganglia and sciatic nerve in type 2 diabetic mice

OBJECTIVE

Peripheral neuropathy is the most common and debilitating complication of type 2 diabetes, leading to sensory loss, dysautonomia, hyperalgesia, and spontaneous noxious sensations. Despite the clinical and economic burden of diabetic neuropathy, no effective treatment is available. More preclinical research must be conducted in order to gain further understanding of the aetiology of the disease and elucidate new therapeutic targets.

METHODS

The proteome of lumbar dorsal root ganglia and sciatic nerve of BKS-db/db mice, which contain a mutation of the leptin receptor and are an established type 2 diabetes model, was characterized for the first time by tandem mass tag labelling and mass spectrometry analysis.

RESULTS

Proteomic analysis showed differentially expressed proteins grouped into functional clusters in db/db peripheral nerves compared to control mice, underlining reduced glycolytic and TCA cycle metabolism, higher lipid catabolism, upregulation of muscle-like proteins in DRG and downregulation in SCN, increased cytoskeleton-related proteins, a mild dysregulation of folding chaperones, activation of acute-phase and inflammatory response, and alterations in glutathione metabolism and oxidative stress related proteins.

CONCLUSIONS

Our data validate previous transcriptomic and metabolomic results and uncover new pathways altered in diabetic neuropathy. Our results point out that energetic deficiency could represent the main mechanism of neurodegeneration observed in diabetic neuropathy. These findings may provide important information to select appropriate targets to develop new therapeutic strategies.

Towards engineering ectomycorrhization into switchgrass bioenergy crops via a lectin receptor-like kinase

Soil-borne microbes can establish compatible relationships with host plants, providing a large variety of nutritive and protective compounds in exchange for photosynthesized sugars. However, the molecular mechanisms mediating the establishment of these beneficial relationships remain unclear. Our previous genetic mapping and whole-genome resequencing studies identified a gene deletion event of a Populus trichocarpa lectin receptor-like kinase gene PtLecRLK1 in Populus deltoides that was associated with poor-root colonization by the ectomycorrhizal fungus Laccaria bicolor. By introducing PtLecRLK1 into a perennial grass known to be a non-host of L. bicolor, switchgrass (Panicum virgatum L.), we found that L. bicolor colonizes ZmUbipro-PtLecRLK1 transgenic switchgrass roots, which illustrates that the introduction of PtLecRLK1 has the potential to convert a non-host to a host of L. bicolor. Furthermore, transcriptomic and proteomic analyses on inoculated-transgenic switchgrass roots revealed genes/proteins overrepresented in the compatible interaction and underrepresented in the pathogenic defence pathway, consistent with the view that pathogenic defence response is down-regulated during compatible interaction. Metabolomic profiling revealed that root colonization in the transgenic switchgrass was associated with an increase in N-containing metabolites and a decrease in organic acids, sugars, and aromatic hydroxycinnamate conjugates, which are often seen in the early steps of establishing compatible interactions. These studies illustrate that PtLecRLK1 is able to render a plant susceptible to colonization by the ectomycorrhizal fungus L. bicolor and shed light on engineering mycorrhizal symbiosis into a non-host to enhance plant productivity and fitness on marginal lands.

Protein Abundance Prediction Through Machine Learning Methods

Proteins are responsible for most physiological processes, and their abundance provides crucial information for systems biology research. However, absolute protein quantification, as determined by mass spectrometry, still has limitations in capturing the protein pool. Protein abundance is impacted by translation kinetics, which rely on features of codons. In this study, we evaluated the effect of codon usage bias of genes on protein abundance. Notably, we observed differences regarding codon usage patterns between genes coding for highly abundant proteins and genes coding for less abundant proteins. Analysis of synonymous codon usage and evolutionary selection showed a clear split between the two groups. Our machine learning models predicted protein abundances from codon usage metrics with remarkable accuracy, achieving strong correlation with experimental data. Upon integration of the predicted protein abundance in enzyme-constrained genome-scale metabolic models, the simulated phenotypes closely matched experimental data, which demonstrates that our predictive models are valuable tools for systems metabolic engineering approaches.

Bovine milk somatic cell transcriptomic response to Staphylococcus aureus is dependent on strain genotype

Background

Mastitis is an economically important disease of dairy cows with Staphylococcus aureus a major cause worldwide. Challenge of Holstein-Friesian cows demonstrated that S. aureus strain MOK124, which belongs to Clonal Complex (CC)151, caused clinical mastitis, while strain MOK023, belonging to CC97, caused mild or subclinical mastitis. The aim of this study was to elucidate the molecular mechanisms of the host immune response utilising a transcriptomic approach. Milk somatic cells were collected from cows infected with either S. aureus MOK023 or MOK124 at 0, 24, 48, 72 and 168 h post-infection (hpi) and analysed for differentially expressed (DE) genes in response to each strain.

Results

In response to MOK023, 1278, 2278, 1986 and 1750 DE genes were found at 24, 48, 72 and 168 hpi, respectively, while 2293, 1979, 1428 and 1544 DE genes were found in response to MOK124 at those time points. Genes involved in milk production (CSN1, CSN10, CSN1S2, CSN2, a-LACTA and PRLR) were downregulated in response to both strains, with a more pronounced decrease in the MOK124 group. Immune response pathways such as NF-κB and TNF signalling were overrepresented in response to both strains at 24 hpi. These immune pathways continued to be overrepresented in the MOK023 group at 48 and 72 hpi, while the Hippo signalling, extracellular matrix interaction (ECM) and tight junction pathways were overrepresented in the MOK124 group between 48 and 168 hpi. Cellular composition analysis demonstrated that a neutrophil response was predominant in response to MOK124, while M1 macrophages were the main milk cell type post-infection in the MOK023 group.

Conclusions

A switch from immune response pathways to pathways involved in maintaining the integrity of the epithelial cell layer was observed in the MOK124 group from 48 hpi, which coincided with the occurrence of clinical signs in the infected animals. The higher proportion of M1 macrophages in the MOK023 group and lack of substantial neutrophil recruitment in response to MOK023 may indicate immune evasion by this strain. The results of this study highlight that the somatic cell transcriptomic response to S. aureus is dependent on the genotype of the infecting strain.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08135-7.

Tendon and multiomics: advantages, advances, and opportunities

Tendons heal by fibrosis, which hinders function and increases re-injury risk. Yet the biology that leads to degeneration and regeneration of tendons is not completely understood. Improved understanding of the metabolic nuances that cause diverse outcomes in tendinopathies is required to solve these problems. 'Omics methods are increasingly used to characterize phenotypes in tissues. Multiomics integrates 'omic datasets to identify coherent relationships and provide insight into differences in molecular and metabolic pathways between anatomic locations, and disease stages. This work reviews the current literature pertaining to multiomics in tendon and the potential of these platforms to improve tendon regeneration. We assessed the literature and identified areas where 'omics platforms contribute to the field: (1) Tendon biology where their hierarchical complexity and demographic factors are studied. (2) Tendon degeneration and healing, where comparisons across tendon pathologies are analyzed. (3) The in vitro engineered tendon phenotype, where we compare the engineered phenotype to relevant native tissues. (4) Finally, we review regenerative and therapeutic approaches. We identified gaps in current knowledge and opportunities for future study: (1) The need to increase the diversity of human subjects and cell sources. (2) Opportunities to improve understanding of tendon heterogeneity. (3) The need to use these improvements to inform new engineered and regenerative therapeutic approaches. (4) The need to increase understanding of the development of tendon pathology. Together, the expanding use of various 'omics platforms and data analysis resulting from these platforms could substantially contribute to major advances in the tendon tissue engineering and regenerative medicine field.

Impact of MiRNA-181a2 on the Clinical Course of IDH1 Wild Type Glioblastoma

Background: Recently, miRNA-181a2 could be identified as a major regulator of IDH1 expression in fat tissue. The IDH1 gene, its mutation and expression have a major impact on overall survival in patients with glioblastoma. The presented study aimed to investigate the effect of miRNA-181a2 on IDH1 expression in glioblastoma and on the prognosis of patients suffering from, for example, a tumor. Methods: A total of 74 glioblastoma specimens were analyzed for the expression of miRNA-181a2, acquired as fold change, using qRT-PCR. IDH1 protein expression was estimated via mRNA quantification. Eight post mortal, non-glioma related brain tissue specimens served as the control group. The results were correlated with relevant demographic and clinical aspects of the cohort. A TCGA dataset was used as an independent reference. Results: MiRNA-181a2 was significantly downregulated in tumor samples compared to the control group (p < 0.001). In the glioblastoma cohort, 63/74 (85.1%) showed an IDH1 wild type, while 11/74 (14.9%) patients harbored an IDH 1 mutation. In patients with IDH1 wild type glioblastoma, low miRNA-181a2 expression correlated with a prolonged overall survival (p = 0.019), also verifiable in an independent TCGA dataset. This correlation could not be identified for patients with an IDH1 mutation. MiRNA-181a2 expression tended to correlate inversely with IDH1 protein expression (p = 0.06). Gross total resection of the tumor was an independent marker for a prolonged survival (p = 0.03). Conclusion: MiRNA-181a2 seems to be a promising prognostic marker of selective glioblastoma patients with IDH1 wild type characteristics. This effect may be mediated via direct regulation of IDH1 expression.

Omics in Systems Biology: Current Progress and Future Outlook

Biological research has undergone tremendous changes over the past three decades. Research used to almost exclusively focus on a single aspect of a single molecule per experiment. Modern technologies have enabled thousands of molecules to be simultaneously analyzed and the way that these molecules influence each other to be discerned. The change is so dramatic that it has given rise to a whole new descriptive suffix (i.e., omics) to describe these fields of study. While genomics was arguably the initial driver of this new trend, it quickly spread to other biological entities resulting in the creation of transcriptomics, proteomics, metabolomics, etc. The development of these "big four omics" created a wave of other omic fields, such as epigenomics, glycomics, lipidomics, microbiomics, and even foodomics; all with the purpose of comprehensively studying all the molecular entities or processes within their respective domain. The large number of omic fields that are invented even led to the term "panomics" as a way to classify them all under one category. Ultimately, all of these omic fields are setting the foundation for developing systems biology; in which the focus will be on determining the complex interactions that occur within biological systems.

Inhaled multi-walled carbon nanotubes differently modulate global gene and protein expression in rat lungs

Inhalation of multi-walled carbon nanotubes (MWCNTs) induces lung inflammation. Depending on industrial applications, CNTs with different physicochemical characteristics are produced and workers can potentially be exposed. This raises concerns about the long-term health effects of these nanomaterials. Because of the wide variety of MWCNTs, it is essential to study the toxicological effects of CNTs of various shapes and to better understand the impact physical and chemical properties have on their toxicity. In this study, rats were exposed by nose-only to two pristine MWCNTs with different morphologies: the long and thick NM-401 or the short and thin NM-403. After four weeks of inhalation, animals were euthanized at four different times during the recovery period: three days (short-term), 30 and 90 days (intermediate-term) and 180 days (long-term). Analyses of the transcriptome in the whole lung and the proteome in the bronchoalveolar lavage fluid of exposed animals were performed to understand the MWCNT underlying mechanisms of toxicity. Following inhalation of NM-401, we observed a dose-dependent increase in the number of differentially expressed genes and proteins, whereas there is no clear difference between the two concentrations of NM-403. After NM-403 inhalation, the number of differentially expressed genes and proteins varied less between the four post-exposure times compared to NM-401, which supports the postulation of a persistent effect of this type of CNT. Our toxicogenomics approaches give insights into the different toxicological profile following MWCNT exposure.

Sex differences in the transcription of glutamate transporters in major depression and suicide

BACKGROUND

Accumulating evidence indicates that the glutamate system contributes to the pathophysiology of major depressive disorder (MDD) and suicide. We previously reported higher mRNA expression of glutamate receptors in the dorsolateral prefrontal cortex (DLPFC) of females with MDD.

METHODS

In the current study, we measured the expression of mRNAs encoding glutamate transporters in the DLPFC of MDD subjects who died by suicide (MDD-S, n = 51), MDD non-suicide subjects (MDD-NS, n = 28), and individuals who did not have a history of neurological illness (CTRL, n = 32).

RESULTS

Females but not males with MDD showed higher expression of EAATs and VGLUTs relative to CTRLs. VGLUT expression was significantly higher in the female MDD-S group, relative to the other groups. EAAT expression was lower in the male violent suicides.

LIMITATIONS

This study has limitations common to most human studies, including medication history and demographic differences between the diagnostic groups. We mitigated the effects of confounders by including them as covariates in our analyses.

CONCLUSIONS

We report sex differences in the expression of glutamate transporter genes in the DLPFC in MDD. Increased neuronal glutamate transporter expression may increase synaptic glutamate, leading to neuronal and glial loss in the DLPFC in MDD. These deficits may lower DLPFC activity, impair problem solving and impair executive function in depression, perhaps increasing vulnerability to suicidal behavior. These data add to accumulating support for the hypothesis that glutamatergic transmission is dysregulated in MDD and suicide. Glutamate transporters may be novel targets for the development of rapidly acting antidepressant therapies.

Global transcriptomic and proteomics analysis of Lactobacillus plantarum Y44 response to 2,2-azobis(2-methylpropionamidine) dihydrochloride (AAPH) stress

Our previous study demonstrated that Lactobacillus plantarum Y44 exhibited antioxidant activity. However, the physiological characteristics of L. plantarum Y44 exposure to oxidative stress was not clear. In this research, the differentially expressed proteins and genes in L. plantarum Y44 under 2,2-azobis(2-methylpropionamidine) dihydrochloride (AAPH) stress at different concentrations were studied by using integrated transcriptomic and proteomic methods. Under 100 mM AAPH stress condition, 1139 differentially expressed genes (DEGs, 546 up-regulated and 593 down-regulated) and 329 differentially expressed proteins (DEPs, 127 up-regulated and 202 down-regulated) were observed. Under 200 mM AAPH stress condition, 1526 DEGs (751 up-regulated and 775 down-regulated) and 382 DEPs (139 up-regulated and 243 down-regulated) were observed. Overall, we found that L. plantarum Y44 fought against AAPH induced oxidative stress by up-regulating antioxidant enzymes and DNA repair proteins, such as ATP-dependent DNA helicase RuvA, adenine DNA glycosylase, single-strand DNA-binding protein SSB, DNA-binding ferritin-like protein DPS, thioredoxin reductase, protein-methionine-S-oxide reductase and glutathione peroxidase. Additionally, cell envelope composition of L. plantarum Y44 was highly remodeled by accelerating peptidoglycan and teichoic-acid (LTA) biosynthesis and modulating the fatty acids (FA) composition to achieve a higher ratio of unsaturated/saturated fatty acids (UFAs/SFAs) against AAPH stress. Moreover, metabolism processes including carbohydrate metabolism, amino acid biosynthesis, and nucleotide metabolism altered to respond to AAPH-induced damage. Altogether, our findings allow us to facilitate a better understanding of L. plantarum Y44 against oxidative stress. SIGNIFICANCE: This study represents an integrated proteomic and transcriptomic analysis of Lactobacillus plantarum Y44 response to 2,2-azobis(2-methylpropionamidine) dihydrochloride (AAPH) stress. Differentially expressed proteins and genes were identified between the proteome and transcriptome of L. plantarum Y44 under different AAPH stress. AAPH-induced response of L. plantarum Y44 appears to be primarily based on ROS scavenging, DNA repair, highly remodeled cell surface and specific metabolic processes. The knowledge about these proteomes and transcriptomes provides significant insights into the oxidative stress response of Lactobacillus plantarum.

Quantitative Proteomics of All 14 Renal Tubule Segments in Rat

BACKGROUND

Previous research has used RNA sequencing in microdissected kidney tubules or single cells isolated from the kidney to profile gene expression in each type of kidney tubule epithelial cell. However, because proteins, not mRNA molecules, mediate most cellular functions, it is desirable to know the identity and amounts of each protein species to understand function. Recent improvements in the sensitivity of mass spectrometers offered us the ability to quantify the proteins expressed in each of 14 different renal tubule segments from rat.

METHODS

We manually dissected kidney tubules from rat kidneys and subjected samples to protein mass spectrometry. We used the "proteomic ruler" technique to estimate the number of molecules of each protein per cell.

RESULTS

Over the 44 samples analyzed, the average number of quantified proteins per segment was 4234, accounting for at least 99% of protein molecules in each cell. We have made the data publicly available online at the Kidney Tubule Expression Atlas website (https://esbl.nhlbi.nih.gov/KTEA/). Protein abundance along the renal tubule for many commonly studied water and solute transport proteins and metabolic enzymes matched expectations from prior localization studies, demonstrating the overall reliability of the data. The site features a "correlated protein" function, which we used to identify cell type-specific transcription factors expressed along the renal tubule.

CONCLUSIONS

We identified and quantified proteins expressed in each of the 14 segments of rat kidney tubules and used the proteomic data that we obtained to create an online information resource, the Kidney Tubule Expression Atlas. This resource will allow users throughout the world to browse segment-specific protein expression data and download them for their own research.

Combined transcriptomics and proteomics forecast analysis for potential genes regulating the Columbian plumage color in chickens

BACKGROUND

Coloration is one of the most recognizable characteristics in chickens, and clarifying the coloration mechanisms will help us understand feather color formation. "Yufen I" is a commercial egg-laying chicken breed in China that was developed by a three-line cross using lines H, N and D. Columbian plumage is a typical feather character of the "Yufen I" H line. To elucidate the molecular mechanism underlying the pigmentation of Columbian plumage, this study utilizes high-throughput sequencing technology to compare the transcriptome and proteome differences in the follicular tissue of different feathers, including the dorsal neck with black and white striped feather follicles (Group A) and the ventral neck with white feather follicles (Group B) in the "Yufen I" H line.

RESULTS

In this study, we identified a total of 21,306 genes and 5,203 proteins in chicken feather follicles. Among these, 209 genes and 382 proteins were differentially expressed in two locations, Group A and Group B, respectively. A total of 8 differentially expressed genes (DEGs) and 9 differentially expressed proteins (DEPs) were found to be involved in the melanogenesis pathway. Additionally, a specifically expressed MED23 gene and a differentially expressed GNAQ protein were involved in melanin synthesis. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis mapped 190 DEGs and 322 DEPs to 175 and 242 pathways, respectively, and there were 166 pathways correlated with both DEGs and DEPs. 49 DEPs/DEGs overlapped and were enriched for 12 pathways. Transcriptomic and proteomic analyses revealed that the following pathways were activated: melanogenesis, cardiomyocyte adrenergic, calcium and cGMP-PKG. The expression of DEGs was validated by real-time quantitative polymerase chain reaction (qRT-PCR) that produced results similar to those from RNA-seq. In addition, we found that the expression of the MED23, FZD10, WNT7B and WNT11 genes peaked at approximately 8 weeks in the "Yufen I" H line, which is consistent with the molting cycle. As both groups showed significant differences in terms of the expression of the studied genes, this work opens up avenues for research in the future to assess their exact function in determining plumage color.

CONCLUSION

Common DEGs and DEPs were enriched in the melanogenesis pathway. MED23 and GNAQ were also reported to play a crucial role in melanin synthesis. In addition, this study is the first to reveal gene and protein variations in in the "Yufen I" H line during Columbian feather color development and to discover principal genes and proteins that will aid in functional genomics studies in the future. The results of the present study provide a significant conceptual basis for the future breeding schemes with the "Yufen I" H line and provide a basis for research on the mechanisms of feather pigmentation.

Development of Teleost Intermuscular Bones Undergoing Intramembranous Ossification Based on Histological-Transcriptomic-Proteomic Data

Intermuscular bones (IBs) specially exist in lower teleost fish and the molecular mechanism for its development remains to be clarified. In this study, different staining methods and comparative proteomics were conducted to investigate the histological structure and proteome of IB development in Megalobrama amblycephala, including four key IB developmental stages (S1-IBs have not emerged in the tail part; S2-several small IBs started to ossify in the tail part; S3-IBs appeared rapidly; S4-all the IBs appeared with mature morphology). Alcian blue and alizarin red S stained results indicated that IBs were gradually formed from S2 to S4, undergoing intramembranous ossification without a cartilaginous phase. A total of 3368 proteins were identified by using the isobaric tags for relative and absolute quantitation (iTRAQ) approach. Functional annotation showed that proteins which were differentially expressed among stages were involved in calcium, MAPK, Wnt, TGF-β, and osteoclast pathways which played a critical role in bone formation and differentiation. Three proteins (collagen9α1, stat1, tnc) associated with chondrocytes did not exhibit significant changes through S2 to S4; however, proteins (entpd5, casq1a, pvalb, anxa2a, anxa5) which associated with osteoblasts and bone formation and differentiation showed significantly a higher expression level from S1 to S2, as well as to S3 and S4. These further demonstrated that development of IBs did not go through a cartilaginous phase. The inhibitors of TGF-β and Wnt pathways were tested on zebrafish (sp7/eGFP) and the results indicated that both inhibitors significantly delayed IB development. This study provides a comprehensive understanding of the IB ossification pattern, which will help further elucidate the molecular mechanisms for IB development in teleosts.

Initiating Events in Direct Cardiomyocyte Reprogramming

Direct reprogramming of fibroblasts into cardiomyocyte-like cells (iCM) holds great potential for heart regeneration and disease modeling and may lead to future therapeutic applications. Currently, application of this technology is limited by our lack of understanding of the molecular mechanisms that drive direct iCM reprogramming. Using a quantitative mass spectrometry-based proteomic approach, we identified the temporal global changes in protein abundance that occur during initial phases of iCM reprogramming. Collectively, our results show systematic and temporally distinct alterations in levels of specific functional classes of proteins during the initiating steps of reprogramming including extracellular matrix proteins, translation factors, and chromatin-binding proteins. We have constructed protein relational networks associated with the initial transition of a fibroblast into an iCM. These findings demonstrate the presence of an orchestrated series of temporal steps associated with dynamic changes in protein abundance in a defined group of protein pathways during the initiating events of direct reprogramming.

Identification of Proteins and Genes Expressed by Methylophaga thiooxydans During Growth on Dimethylsulfide and Their Presence in Other Members of the Genus

Dimethylsulfide is a volatile organic sulfur compound that provides the largest input of biogenic sulfur from the oceans to the atmosphere, and thence back to land, constituting an important link in the global sulfur cycle. Microorganisms degrading DMS affect fluxes of DMS in the environment, but the underlying metabolic pathways are still poorly understood. Methylophaga thiooxydans is a marine methylotrophic bacterium capable of growth on DMS as sole source of carbon and energy. Using proteomics and transcriptomics we identified genes expressed during growth on dimethylsulfide and methanol to refine our knowledge of the metabolic pathways that are involved in DMS and methanol degradation in this strain. Amongst the most highly expressed genes on DMS were the two methanethiol oxidases driving the oxidation of this reactive and toxic intermediate of DMS metabolism. Growth on DMS also increased expression of the enzymes of the tetrahydrofolate linked pathway of formaldehyde oxidation, in addition to the tetrahydromethanopterin linked pathway. Key enzymes of the inorganic sulfur oxidation pathway included flavocytochrome c sulfide dehydrogenase, sulfide quinone oxidoreductase, and persulfide dioxygenases. A sulP permease was also expressed during growth on DMS. Proteomics and transcriptomics also identified a number of highly expressed proteins and gene products whose function is currently not understood. As the identity of some enzymes of organic and inorganic sulfur metabolism previously detected in Methylophaga has not been characterized at the genetic level yet, highly expressed uncharacterized genes provide new targets for further biochemical and genetic analysis. A pan-genome analysis of six available Methylophaga genomes showed that only two of the six investigated strains, M. thiooxydans and M. sulfidovorans have the gene encoding methanethiol oxidase, suggesting that growth on methylated sulfur compounds of M. aminisulfidivorans is likely to involve different enzymes and metabolic intermediates. Hence, the pathways of DMS-utilization and subsequent C1 and sulfur oxidation are not conserved across Methylophaga isolates that degrade methylated sulfur compounds.

Gene expression variability: the other dimension in transcriptome analysis

Transcriptome sequencing is a powerful technique to study molecular changes that underlie the differences in physiological conditions and disease progression. A typical question that is posed in such studies is finding genes with significant changes between sample groups. In this respect expression variability is regarded as a nuisance factor that is primarily of technical origin and complicates the data analysis. However, it is becoming apparent that the biological variation in gene expression might be an important molecular phenotype that can affect physiological parameters. In this review we explore the recent literature on technical and biological variability in gene expression, sources of expression variability, (epi-)genetic hallmarks, and evolutionary constraints in genes with robust and variable gene expression. We provide an overview of recent findings on effects of external cues, such as diet and aging, on expression variability and on other biological phenomena that can be linked to it. We discuss metrics and tools that were developed for quantification of expression variability and highlight the importance of future studies in this direction. To assist the adoption of expression variability analysis, we also provide a detailed description and computer code, which can easily be utilized by other researchers. We also provide a reanalysis of recently published data to highlight the value of the analysis method.

Transcriptional and Proteomic Choreography Under Phosphorus Deficiency and Re-supply in the N2 Fixing Cyanobacterium Trichodesmium erythraeum

The N₂ fixing cyanobacterium Trichodesmium is a critically important organism in oligotrophic marine ecosystems, supplying “new” nitrogen (N) to the otherwise N-poor tropical and subtropical regions where it occurs. Low concentrations of phosphorus (P) in these regions can constrain Trichodesmium distribution and N₂ fixation rates. Physiological characterization of a single species in a mixed community can be challenging, and ‘omic approaches are increasingly important tools for tracking nutritional physiology in a taxon-specific manner. As such, studies examining the dynamics of gene and protein markers of physiology (e.g., nutrient stress) are critical for the application and interpretation of such ‘omic data in situ. Here we leveraged combined transcriptomics, proteomics, and enzyme activity assays to track the physiological response of Trichodesmium erythraeum IMS101 to P deficiency and subsequent P re-supply over 72 h of sampling. P deficiency resulted in differential gene expression, protein abundance, and enzyme activity that highlighted a synchronous shift in P physiology with increases in the transcripts and corresponding proteins for hydrolyzing organic phosphorus, taking up phosphate with higher affinity, and modulating intracellular P demand. After P deficiency was alleviated, gene expression of these biomarkers was reduced to replete levels within 4 h of P amendment. A number of these gene biomarkers were adjacent to putative pho boxes and their expression patterns were similar to a sphR response regulator. Protein products of the P deficiency biomarkers were slow to decline, with 84% of the original P deficient protein set still significantly differentially expressed after 72 h. Alkaline phosphatase activity tracked with proteins for this enzyme. With the rapid turnover time of transcripts, they appear to be good biomarkers of a P stress phenotype, whereas proteins, with a slower turnover time, may better reflect cellular activities. These results highlight the importance of validating and pairing transcriptome and proteome data that can be applied to physiological studies of key species in situ.

Poor transcript-protein correlation in the brain: negatively correlating gene products reveal neuronal polarity as a potential cause

Transcription, translation, and turnover of transcripts and proteins are essential for cellular function. The contribution of those factors to protein levels is under debate, as transcript levels and cognate protein levels do not necessarily correlate due to regulation of translation and protein turnover. Here we propose neuronal polarity as a third factor that is particularly evident in the CNS, leading to considerable distances between somata and axon terminals. Consequently, transcript levels may negatively correlate with cognate protein levels in CNS regions, i.e., transcript and protein levels behave reciprocally. To test this hypothesis, we performed an integrative inter-omics study and analyzed three interconnected rat auditory brainstem regions (cochlear nuclear complex, CN; superior olivary complex, SOC; inferior colliculus, IC) and the rest of the brain as a reference. We obtained transcript and protein sets in these regions of interest (ROIs) by DNA microarrays and label-free mass spectrometry, and performed principal component and correlation analyses. We found 508 transcript|protein pairs and detected poor to moderate transcript|protein correlation in all ROIs, as evidenced by coefficients of determination from 0.34 to 0.54. We identified 57-80 negatively correlating gene products in the ROIs and intensively analyzed four of them for which the correlation was poorest. Three cognate proteins (Slc6a11, Syngr1, Tppp) were synaptic and hence candidates for a negative correlation because of protein transport into axon terminals. Thus, we systematically analyzed the negatively correlating gene products. Gene ontology analyses revealed overrepresented transport/synapse-related proteins, supporting our hypothesis. We present 30 synapse/transport-related proteins with poor transcript|protein correlation. In conclusion, our analyses support that protein transport in polar cells is a third factor that influences the protein level and, thereby, the transcript|protein correlation. OPEN SCIENCE BADGES: This article has received a badge for *Open Materials* and *Open Data* because it provided all relevant information to reproduce the study in the manuscript and because it made the data publicly available. The data can be accessed at https://osf.io/ha28n/. The complete Open Science Disclosure form for this article can be found at the end of the article. More information about the Open Practices badges can be found at https://cos.io/our-services/open-science-badges/.

Proteomic-based approaches to cardiac development and disease

Congenital malformations, or structural birth defects, are now the leading cause of infant mortality in the United States and Europe (Dolk et al., 2010; Heron et al., 2009). Of the congenital malformations, congenital heart disease (CHD) is the most common (Dolk et al., 2010; Heron et al., 2009). Thus, a molecular understanding of heart development is an essential goal for improving clinical approaches to CHD. However, CHDs are commonly a result of genetic defects that manifest themselves in a spatial and temporal manner during the early stages of embryogenesis, leaving them mostly intractable to mass spectrometry-based analysis. Here, we describe the technologies and advancements in the field of mass spectrometry over the past few years that have begun to provide insights into the molecular and cellular basis of CHD and prospects for these types of approaches in the future.

Sliced inverse regression for integrative multi-omics data analysis

Advancement in next-generation sequencing, transcriptomics, proteomics and other high-throughput technologies has enabled simultaneous measurement of multiple types of genomic data for cancer samples. These data together may reveal new biological insights as compared to analyzing one single genome type data. This study proposes a novel use of supervised dimension reduction method, called sliced inverse regression, to multi-omics data analysis to improve prediction over a single data type analysis. The study further proposes an integrative sliced inverse regression method (integrative SIR) for simultaneous analysis of multiple omics data types of cancer samples, including MiRNA, MRNA and proteomics, to achieve integrative dimension reduction and to further improve prediction performance. Numerical results show that integrative analysis of multi-omics data is beneficial as compared to single data source analysis, and more importantly, that supervised dimension reduction methods possess advantages in integrative data analysis in terms of classification and prediction as compared to unsupervised dimension reduction methods.

Domestic Fowl Breed Variation in Egg White Protein Expression: Application of Proteomics and Transcriptomics

Avian egg white is essential for protecting and nourishing bird embryos during their development. Being produced in the female magnum, variability in hen oviduct gene expression may affect egg white composition in domestic chickens. Since traditional poultry breeds may represent a source of variation, in the present study we describe the egg white proteome (mass spectrometry) and corresponding magnum transcriptome (high-throughput sequencing) for 20 hens from five domestic fowl breeds (large breeds: Araucana, Czech golden pencilled, Minorca; and small breeds: Booted bantam, Rosecomb bantam). In total, we identified 189 egg white proteins and 16391 magnum-expressed genes. The majority of egg white protein content comprised proteins with an antimicrobial function. Despite general similarity, Between-class Principal Component Analysis revealed significant breed-specific variability in protein abundances, differentiating especially small and large breeds. Though we found strong association between magnum mRNA expression and egg white protein abundance across genes, coinertia analysis revealed no transcriptome/proteome costructure at the individual level. Our study is the first to show variation in protein abundances in egg white across chicken breeds with potential effects on egg quality, biosafety, and chick development. The observed interindividual variation probably results from post-transcriptional regulation creating a discrepancy between proteomic and transcriptomic data.

Predicting bacterial growth conditions from mRNA and protein abundances

Cells respond to changing nutrient availability and external stresses by altering the expression of individual genes. Condition-specific gene expression patterns may thus provide a promising and low-cost route to quantifying the presence of various small molecules, toxins, or species-interactions in natural environments. However, whether gene expression signatures alone can predict individual environmental growth conditions remains an open question. Here, we used machine learning to predict 16 closely-related growth conditions using 155 datasets of E. coli transcript and protein abundances. We show that models are able to discriminate between different environmental features with a relatively high degree of accuracy. We observed a small but significant increase in model accuracy by combining transcriptome and proteome-level data, and we show that measurements from stationary phase cells typically provide less useful information for discriminating between conditions as compared to exponentially growing populations. Nevertheless, with sufficient training data, gene expression measurements from a single species are capable of distinguishing between environmental conditions that are separated by a single environmental variable.

Module-detection approaches for the integration of multilevel omics data highlight the comprehensive response of Aspergillus fumigatus to caspofungin

Background

Omics data provide deep insights into overall biological processes of organisms. However, integration of data from different molecular levels such as transcriptomics and proteomics, still remains challenging. Analyzing lists of differentially abundant molecules from diverse molecular levels often results in a small overlap mainly due to different regulatory mechanisms, temporal scales, and/or inherent properties of measurement methods. Module-detecting algorithms identifying sets of closely related proteins from protein-protein interaction networks (PPINs) are promising approaches for a better data integration.

Results

Here, we made use of transcriptome, proteome and secretome data from the human pathogenic fungus Aspergillus fumigatus challenged with the antifungal drug caspofungin. Caspofungin targets the fungal cell wall which leads to a compensatory stress response. We analyzed the omics data using two different approaches: First, we applied a simple, classical approach by comparing lists of differentially expressed genes (DEGs), differentially synthesized proteins (DSyPs) and differentially secreted proteins (DSePs); second, we used a recently published module-detecting approach, ModuleDiscoverer, to identify regulatory modules from PPINs in conjunction with the experimental data. Our results demonstrate that regulatory modules show a notably higher overlap between the different molecular levels and time points than the classical approach. The additional structural information provided by regulatory modules allows for topological analyses. As a result, we detected a significant association of omics data with distinct biological processes such as regulation of kinase activity, transport mechanisms or amino acid metabolism. We also found a previously unreported increased production of the secondary metabolite fumagillin by A. fumigatus upon exposure to caspofungin. Furthermore, a topology-based analysis of potential key factors contributing to drug-caused side effects identified the highly conserved protein polyubiquitin as a central regulator. Interestingly, polyubiquitin UbiD neither belonged to the groups of DEGs, DSyPs nor DSePs but most likely strongly influenced their levels.

Conclusion

Module-detecting approaches support the effective integration of multilevel omics data and provide a deep insight into complex biological relationships connecting these levels. They facilitate the identification of potential key players in the organism’s stress response which cannot be detected by commonly used approaches comparing lists of differentially abundant molecules.

Electronic supplementary material

The online version of this article (10.1186/s12918-018-0620-8) contains supplementary material, which is available to authorized users.

Kinetic Modeling of Virus Growth in Cells

When a virus infects a host cell, it hijacks the biosynthetic capacity of the cell to produce virus progeny, a process that may take less than an hour or more than a week. The overall time required for a virus to reproduce depends collectively on the rates of multiple steps in the infection process, including initial binding of the virus particle to the surface of the cell, virus internalization and release of the viral genome within the cell, decoding of the genome to make viral proteins, replication of the genome, assembly of progeny virus particles, and release of these particles into the extracellular environment. For a large number of virus types, much has been learned about the molecular mechanisms and rates of the various steps. However, in only relatively few cases during the last 50 years has an attempt been made-using mathematical modeling-to account for how the different steps contribute to the overall timing and productivity of the infection cycle in a cell. Here we review the initial case studies, which include studies of the one-step growth behavior of viruses that infect bacteria (Qβ, T7, and M13), human immunodeficiency virus, influenza A virus, poliovirus, vesicular stomatitis virus, baculovirus, hepatitis B and C viruses, and herpes simplex virus. Further, we consider how such models enable one to explore how cellular resources are utilized and how antiviral strategies might be designed to resist escape. Finally, we highlight challenges and opportunities at the frontiers of cell-level modeling of virus infections.

New developments in transplant proteomics

PURPOSE OF REVIEW

Despite modern immunosuppression, renal allograft rejection remains a major contributor to graft loss. Novel biomarkers may help improve posttransplant outcomes through the early detection and treatment of rejection. Our objective is to provide an overview of proteomics, review recent discovery-based rejection studies, and explore innovative approaches in biomarker development.

RECENT FINDINGS

Urine MMP7 was identified as a biomarker of subclinical and clinical rejection using two-dimensional liquid chromatography tandem-mass spectrometry (LC-MS/MS) and improved the overall diagnostic discrimination of urine CXCL10 : Cr alone for renal allograft inflammation. A novel peptide signature to classify stable allografts from acute rejection, chronic allograft injury, and polyoma virus (BKV) nephropathy was identified using isobaric tag for relative and absolute quantitation (TRAQ) and label-free MS, with independent validation by selected reaction monitoring mass spectrometry (SRM-MS). Finally, an in-depth exploration of peripheral blood mononuclear cells identified differential proteoform expression in healthy transplants versus rejection.

SUMMARY

There is still much in the human proteome that remains to be explored, and further integration of renal, urinary, and exosomal data may offer deeper insight into the pathophysiology of rejection. Functional proteomics may be more biologically relevant than protein/peptide quantity alone, such as assessment of proteoforms or activity-based protein profiling. Discovery-based studies have identified potential biomarker candidates, but external validation studies are required.

Nature's fat-burning machine: brown adipose tissue in a hibernating mammal

Brown adipose tissue (BAT) is a unique thermogenic tissue in mammals that rapidly produces heat via nonshivering thermogenesis. Small mammalian hibernators have evolved the greatest capacity for BAT because they use it to rewarm from hypothermic torpor numerous times throughout the hibernation season. Although hibernator BAT physiology has been investigated for decades, recent efforts have been directed toward understanding the molecular underpinnings of BAT regulation and function using a variety of methods, from mitochondrial functional assays to 'omics' approaches. As a result, the inner-workings of hibernator BAT are now being illuminated. In this Review, we discuss recent research progress that has identified players and pathways involved in brown adipocyte differentiation and maturation, as well as those involved in metabolic regulation. The unique phenotype of hibernation, and its reliance on BAT to generate heat to arouse mammals from torpor, has uncovered new molecular mechanisms and potential strategies for biomedical applications.

Evaluation of the ethanol tolerance for wild and mutant Synechocystis strains by flow cytometry

Flow cytometry was used to evaluate the effect of initial ethanol concentrations on cyanobacterial strains of Synechocystis PCC 6803 [wild-type (WT), and ethanol producing recombinants (UL 004 and UL 030)] in batch cultures. Ethanol recombinants, containing one or two metabolically engineered cassettes, were designed towards the development of an economically competitive process for the direct production of bioethanol from microalgae through an exclusive autotrophic route. It can be concluded that the recombinant Synechocystis UL 030 containing two copies of the genes per genome was the most tolerant to ethanol. Nevertheless, to implement a production process using recombinant strains, the bioethanol produced will be required to be continuously extracted from the culture media via a membrane-based technological process for example to prevent detrimental effects on the biomass. The results presented here are of significance in defining the maximum threshold for bulk ethanol concentration in production media.

Rational design of a synthetic Entner-Doudoroff pathway for enhancing glucose transformation to isobutanol in Escherichia coli

Isobutanol as a more desirable biofuel has attracted much attention. In our previous work, an isobutanol-producing strain Escherichia coli LA09 had been obtained by rational redox status improvement under guidance of the genome-scale metabolic model. However, the low transformation from sugar to isobutanol is a limiting factor for isobutanol production by E. coli LA09. In this study, the intracellular metabolic profiles of the isobutanol-producing E. coli LA09 with different initial glucose concentrations were investigated and the metabolic reaction of fructose 6-phosphate to 1, 6-diphosphate fructose in glycolytic pathway was identified as the rate-limiting step of glucose transformation. Thus, redesigned carbon catabolism was implemented by altering flux of sugar metabolism. Here, the heterologous Entner-Doudoroff (ED) pathway from Zymomonas mobilis was constructed, and the adaptation of upper and lower parts of ED pathway was further improved with artificial promoters to alleviate the accumulation of toxic intermediate metabolite 2-keto-3-deoxy-6-phospho-gluconate (KDPG). Finally, the best isobutanol-producing E. coli ED02 with higher glucose transformation and isobutanol production was obtained. In the fermentation of strain E. coli ED02 with 45 g/L initial glucose, the isobutanol titer, yield and average producing rate were, respectively, increased by 56.8, 47.4 and 88.1% to 13.67 g/L, 0.50 C-mol/C-mol and 0.456 g/(L × h) in a shorter time of 30 h, compared with that of the starting strain E. coli LA09.

Staphylococcus aureus Responds to the Central Metabolite Pyruvate To Regulate Virulence

Staphylococcus aureus is a versatile bacterial pathogen that can cause significant disease burden and mortality. Like other pathogens, S. aureus must adapt to its environment to produce virulence factors to survive the immune responses evoked by infection. Despite the importance of environmental signals for S. aureus pathogenicity, only a limited number of these signals have been investigated in detail for their ability to modulate virulence. Here we show that pyruvate, a central metabolite, causes alterations in the overall metabolic flux of S. aureus and enhances its pathogenicity. We demonstrate that pyruvate induces the production of virulence factors such as the pore-forming leucocidins and that this induction results in increased virulence of community-acquired methicillin-resistant S. aureus (CA-MRSA) clone USA300. Specifically, we show that an efficient “pyruvate response” requires the activation of S. aureus master regulators AgrAC and SaeRS as well as the ArlRS two-component system. Altogether, our report further establishes a strong relationship between metabolism and virulence and identifies pyruvate as a novel regulatory signal for the coordination of the S. aureus virulon through intricate regulatory networks.

Delineation of the influence of host-derived small molecules on the makeup of human pathogens is a growing field in understanding host-pathogen interactions. S. aureus is a prominent pathogen that colonizes up to one-third of the human population and can cause serious infections that result in mortality in ~15% of cases. Here, we show that pyruvate, a key nutrient and central metabolite, causes global changes to the metabolic flux of S. aureus and activates regulatory networks that allow significant increases in the production of leucocidins. These and other virulence factors are critical for S. aureus to infect diverse host niches, initiate infections, and effectively subvert host immune responses. Understanding how environmental signals, particularly ones that are essential to and prominent in the human host, affect virulence will allow us to better understand pathogenicity and consider more-targeted approaches to tackling the current S. aureus epidemic.