Key Proteomics Tools for Fundamental and Applied Microalgal Research

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

Spatial transcriptomic patterns underlying amyloid-β and tau pathology are associated with cognitive dysfunction in Alzheimer's disease

Amyloid-β (Aβ) and tau proteins accumulate within distinct neuronal systems in Alzheimer's disease (AD). Although it is not clear why certain brain regions are more vulnerable to Aβ and tau pathologies than others, gene expression may play a role. We study the association between brain-wide gene expression profiles and regional vulnerability to Aβ (gene-to-Aβ associations) and tau (gene-to-tau associations) pathologies by leveraging two large independent AD cohorts. We identify AD susceptibility genes and gene modules in a gene co-expression network with expression profiles specifically related to regional vulnerability to Aβ and tau pathologies in AD. In addition, we identify distinct biochemical pathways associated with the gene-to-Aβ and the gene-to-tau associations. These findings may explain the discordance between regional Aβ and tau pathologies. Finally, we propose an analytic framework, linking the identified gene-to-pathology associations to cognitive dysfunction in AD at the individual level, suggesting potential clinical implication of the gene-to-pathology associations.

Relationship between Biochemical Pathways and Non-Coding RNAs Involved in the Progression of Diabetic Retinopathy

Diabetic retinopathy (DR) is a progressive blinding disease, which affects the vision and quality of life of patients, and it severely impacts the society. This complication, caused by abnormal glucose metabolism, leads to structural, functional, molecular, and biochemical abnormalities in the retina. Oxidative stress and inflammation also play pivotal roles in the pathogenic process of DR, leading to mitochondrial damage and a decrease in mitochondrial function. DR causes retinal degeneration in glial and neural cells, while the disappearance of pericytes in retinal blood vessels leads to alterations in vascular regulation and stability. Clinical changes include dilatation and blood flow changes in response to the decrease in retinal perfusion in retinal blood vessels, leading to vascular leakage, neovascularization, and neurodegeneration. The loss of vascular cells in the retina results in capillary occlusion and ischemia. Thus, DR is a highly complex disease with various biological factors, which contribute to its pathogenesis. The interplay between biochemical pathways and non-coding RNAs (ncRNAs) is essential for understanding the development and progression of DR. Abnormal expression of ncRNAs has been confirmed to promote the development of DR, suggesting that ncRNAs such as miRNAs, lncRNAs, and circRNAs have potential as diagnostic biomarkers and theranostic targets in DR. This review provides an overview of the interactions between abnormal biochemical pathways and dysregulated expression of ncRNAs under the influence of hyperglycemic environment in DR.

Breast cancer and its therapeutic targets: A comprehensive review

Breast cancer is a common and deadly disease, so there is a constant need for research to find efficient targets and therapeutic approaches. Breast cancer can be classified on a molecular and histological base. Breast cancer can be divided into ER (estrogen receptor)-positive and ER-negative, HER2 (human epidermal growth factor receptor2)-positive and HER2-negative subtypes based on the presence of specific biomarkers. Targeting hormone receptors, such as the HER2, progesterone receptor (PR), and ER, is very significant and plays a vital role in the onset and progression of breast cancer. Endocrine treatments and HER2-targeted drugs are examples of targeted therapies now being used against these receptors. Emerging immune-based medicines with promising outcomes in the treatment of breast cancer include immune checkpoint inhibitors, cancer vaccines, and adoptive T-cell therapy. It is also explored how immune cells and the tumor microenvironment affect breast cancer development and treatment response. The major biochemical pathways, signaling cascades, and DNA repair mechanisms that are involved in the development and progression of breast cancer, include the PI3K/AKT/mTOR system, the MAPK pathway, and others. These pathways are intended to be inhibited by a variety of targeted drugs, which are then delivered with the goal of restoring normal cellular function. This review aims to shed light on types of breast cancer with the summarization of different therapeutic approaches which can target different pathways for tailored medicines and better patient outcomes.

Impact of renal tubular Cpt1a overexpression on the kidney metabolome in the folic acid-induced fibrosis mouse model

Background: Chronic kidney disease (CKD) is characterized by the progressive and irreversible deterioration of kidney function and structure with the appearance of renal fibrosis. A significant decrease in mitochondrial metabolism, specifically a reduction in fatty acid oxidation (FAO) in tubular cells, is observed in tubulointerstitial fibrosis, whereas FAO enhancement provides protection. Untargeted metabolomics offers the potential to provide a comprehensive analysis of the renal metabolome in the context of kidney injury. Methodology: Renal tissue from a carnitine palmitoyl transferase 1a (Cpt1a) overexpressing mouse model, which displays enhanced FAO in the renal tubule, subjected to folic acid nephropathy (FAN) was studied through a multiplatform untargeted metabolomics approach based on LC-MS, CE-MS and GC-MS analysis to achieve the highest coverage of the metabolome and lipidome affected by fibrosis. The expression of genes related to the biochemical routes showing significant changes was also evaluated. Results: By combining different tools for signal processing, statistical analysis and feature annotation, we were able to identify variations in 194 metabolites and lipids involved in many metabolic routes: TCA cycle, polyamines, one-carbon metabolism, amino acid metabolism, purine metabolism, FAO, glycerolipids and glycerophospholipids synthesis and degradation, glycosphingolipids interconversion, and sterol metabolism. We found several metabolites strongly altered by FAN, with no reversion induced by Cpt1a overexpression (v.g. citric acid), whereas other metabolites were influenced by CPT1A-induced FAO (v.g. glycine-betaine). Conclusion: It was implemented a successful multiplatform metabolomics approach for renal tissue analysis. Profound metabolic changes accompany CKD-associated fibrosis, some associated with tubular FAO failure. These results highlight the importance of addressing the crosstalk between metabolism and fibrosis when undertaking studies attempting to elucidate the mechanism of CKD progression.

Understanding Snail Mucus Biosynthesis and Shell Biomineralisation through Genomic Data Mining of the Reconstructed Carbohydrate and Glycan Metabolic Pathways of the Giant African Snail (Achatina fulica)

The giant African snail (Order Stylommatophora: Family Achatinidae), Achatina fulica (Bowdich, 1822), is the most significant and invasive land snail pest. The ecological adaptability of this snail involves high growth rate, reproductive capacity, and shell and mucus production, driven by several biochemical processes and metabolism. The available genomic information for A. fulica provides excellent opportunities to hinder the underlying processes of adaptation, mainly carbohydrate and glycan metabolic pathways toward the shell and mucus formation. The authors analysed the 1.78 Gb draft genomic contigs of A. fulica to identify enzyme-coding genes and reconstruct biochemical pathways related to the carbohydrate and glycan metabolism using a designed bioinformatic workflow. Three hundred and seventy-seven enzymes involved in the carbohydrate and glycan metabolic pathways were identified based on the KEGG pathway reference in combination with protein sequence comparison, structural analysis, and manual curation. Fourteen complete pathways of carbohydrate metabolism and seven complete pathways of glycan metabolism supported the nutrient acquisition and production of the mucus proteoglycans. Increased copy numbers of amylases, cellulases, and chitinases highlighted the snail advantage in food consumption and fast growth rate. The ascorbate biosynthesis pathway identified from the carbohydrate metabolic pathways of A. fulica was involved in the shell biomineralisation process in association with the collagen protein network, carbonic anhydrases, tyrosinases, and several ion transporters. Thus, our bioinformatic workflow was able to reconstruct carbohydrate metabolism, mucus biosynthesis, and shell biomineralisation pathways from the A. fulica genome and transcriptome data. These findings could reveal several evolutionary advantages of the A. fulica snail, and will benefit the discovery of valuable enzymes for industrial and medical applications.

The Production of Pyruvate in Biological Technology: A Critical Review

Pyruvic acid has numerous applications in the food, chemical, and pharmaceutical industries. The high costs of chemical synthesis have prevented the extensive use of pyruvate for many applications. Metabolic engineering and traditional strategies for mutation and selection have been applied to microorganisms to enhance their ability to produce pyruvate. In the past decades, different microbial strains were generated to enhance their pyruvate production capability. In addition to the development of genetic engineering and metabolic engineering in recent years, the metabolic transformation of wild-type yeast, E. coli, and so on to produce high-yielding pyruvate strains has become a hot spot. The strategy and the understanding of the central metabolism directly related to pyruvate production could provide valuable information for improvements in fermentation products. One of the goals of this review was to collect information regarding metabolically engineered strains and the microbial fermentation processes used to produce pyruvate in high yield and productivity.

Biochemical pathways and associated microbial process of di-2-ethyl hexyl phthalate (DEHP) enhanced degradation by the immobilization technique in sequencing batch reactor

A bacterial strain ASLT-13 was successfully isolated from activated sludge and identified as Pseudomonas amygdali. Gas chromatograph-mass spectrometer (GC-MS) analysis indicated that strain ASLT-13 could completely mineralize di 2-ethyl hexyl phthalate (DEHP). DEHP was first metabolized from the longer side chain of the benzene ring into shorter branches (Phatlalic mono-esters) like Dibutyl phthalate (DBP) under the action of degrading genes. DBP was then converted into di-methyl phthalate (DMP), and then hydrolysed to phthalic acid (PA). PA was eventually converted to CO₂ and H₂O through the TCA cycle. The optimal conditions for immobilization were the sodium alginate (SA) concentration of 6%, CaCl₂ concentration of 5%, ratio of bacteria and SA of 1:1, crosslinking time of 6 h. Bacterial quantity and community structure in sequencing batch reactors (SBRs) was investigated by q-PCR and high-throughput sequencing. The results indicated that DEHP removal efficiency was significantly enhanced by immobilization. Arthrobacter, Acinetobacter, Bacillus and Rhodococcus were the predominant genera for DEHP degradation. This study suggested that the cell immobilization technology had a potential application in DEHP wastewater treatment.

Application of metabolite set enrichment analysis on untargeted metabolomics data prioritises relevant pathways and detects novel biomarkers for inherited metabolic disorders

Untargeted metabolomics (UM) allows for the simultaneous measurement of hundreds of metabolites in a single analytical run. The sheer amount of data generated in UM hampers its use in patient diagnostics because manual interpretation of all features is not feasible. Here, we describe the application of a pathway-based metabolite set enrichment analysis method to prioritise relevant biological pathways in UM data. We validate our method on a set of 55 patients with a diagnosed inherited metabolic disorder (IMD) and show that it complements feature-based prioritisation of biomarkers by placing the features in a biological context. In addition, we find that by taking enriched pathways shared across different IMDs, we can identify common drugs and compounds that could otherwise obscure genuine disease biomarkers in an enrichment method. Finally, we demonstrate the potential of this method to identify novel candidate biomarkers for known IMDs. Our results show the added value of pathway-based interpretation of UM data in IMD diagnostics context.

Mechanisms Involved in Neuroprotective Effects of Transcranial Magnetic Stimulation

Transcranial Magnetic Stimulation (TMS) is widely used in neurophysiology to study cortical excitability. Research over the last few decades has highlighted its added value as a potential therapeutic tool in the treatment of a broad range of psychiatric disorders. More recently, a number of studies have reported beneficial and therapeutic effects for TMS in neurodegenerative conditions and strokes. Yet, despite its recognised clinical applications and considerable research using animal models, the molecular and physiological mechanisms through which TMS exerts its beneficial and therapeutic effects remain unclear. They are thought to involve biochemical-molecular events affecting membrane potential and gene expression. In this aspect, the dopaminergic system plays a special role. This is the most directly and selectively modulated neurotransmitter system, producing an increase in the flux of dopamine (DA) in various areas of the brain after the application of repetitive TMS (rTMS). Other neurotransmitters, such as glutamate and gamma-aminobutyric acid (GABA) have shown a paradoxical response to rTMS. In this way, their levels increased in the hippocampus and striatum but decreased in the hypothalamus and remained unchanged in the mesencephalon. Similarly, there are sufficient evidence that TMS up-regulates the gene expression of BDNF (one of the main brain neurotrophins). Something similar occurs with the expression of genes such as c-Fos and zif268 that encode trophic and regenerative action neuropeptides. Consequently, the application of TMS can promote the release of molecules involved in neuronal genesis and maintenance. This capacity may mean that TMS becomes a useful therapeutic resource to antagonize processes that underlie the previously mentioned neurodegenerative conditions.

Mechanobiology of Colorectal Cancer

Simple Summary

It is well documented that colorectal cancer (CRC) is the third most common cancer type, responsible for high mortality in developed countries, resulting in a high socio-economic impact. Several biochemical and gene expression pathways explaining the manifestation of this cancer in humans have already been identified. However, explanations for some of the related biophysical mechanisms and their influence on CRC remain elusive. In CRC, biophysics and medical research have already revealed the importance of studying the effects of the stiffness and viscoelasticity of the substrate on cells, as well as the effect of the shear stress of blood and lymphatic vessels on the behavior of cells and tissues. A deeper understanding of the relationship between the biophysical cues and biochemical signals could be advantageous to develop new diagnostic techniques and therapeutic strategies. Being a disease with a high mortality rate, it becomes crucial to dedicate efforts to finding effective, alternative therapeutic strategies.

Abstract

In this review, the mechanobiology of colorectal cancer (CRC) are discussed. Mechanotransduction of CRC is addressed considering the relationship of several biophysical cues and biochemical pathways. Mechanobiology is focused on considering how it may influence epithelial cells in terms of motility, morphometric changes, intravasation, circulation, extravasation, and metastization in CRC development. The roles of the tumor microenvironment, ECM, and stroma are also discussed, taking into account the influence of alterations and surface modifications on mechanical properties and their impact on epithelial cells and CRC progression. The role of cancer-associated fibroblasts and the impact of flow shear stress is addressed in terms of how it affects CRC metastization. Finally, some insights concerning how the knowledge of biophysical mechanisms may contribute to the development of new therapeutic strategies and targeting molecules and how mechanical changes of the microenvironment play a role in CRC disease are presented.

Biochemical Mapping of Pyrodinium bahamense Unveils Molecular Underpinnings behind Organismal Processes

Proteins, lipids, and carbohydrates from the harmful algal bloom (HAB)-causing organism Pyrodinium bahamense were characterized to obtain insights into the biochemical processes in this environmentally relevant dinoflagellate. Shotgun proteomics using label-free quantitation followed by proteome mapping using the P. bahamense transcriptome and translated protein databases of Marinovum algicola, Alexandrium sp., Cylindrospermopsis raciborskii, and Symbiodinium kawagutii for annotation enabled the characterization of the proteins in P. bahamense. The highest number of annotated hits were obtained from M. algicola and highlighted the contribution of microorganisms associated with P. bahamense. Proteins involved in dimethylsulfoniopropionate (DMSP) degradation such as propionyl CoA synthethase and acryloyl-CoA reductase were identified, suggesting the DMSP cleavage pathway as the preferred route in this dinoflagellate. Most of the annotated proteins were involved in amino acid biosynthesis and carbohydrate degradation and metabolism, indicating the active roles of these molecules in the vegetative stage of P. bahamense. This characterization provides baseline information on the cellular machinery and the molecular basis of the ecophysiology of P. bahamense.

Pathway-extended gene expression signatures integrate novel biomarkers that improve predictions of patient responses to kinase inhibitors

Cancer chemotherapy responses have been related to multiple pharmacogenetic biomarkers, often for the same drug. This study utilizes machine learning to derive multi‐gene expression signatures that predict individual patient responses to specific tyrosine kinase inhibitors, including erlotinib, gefitinib, sorafenib, sunitinib, lapatinib and imatinib. Support vector machine (SVM) learning was used to train mathematical models that distinguished sensitivity from resistance to these drugs using a novel systems biology‐based approach. This began with expression of genes previously implicated in specific drug responses, then expanded to evaluate genes whose products were related through biochemical pathways and interactions. Optimal pathway‐extended SVMs predicted responses in patients at accuracies of 70% (imatinib), 71% (lapatinib), 83% (sunitinib), 83% (erlotinib), 88% (sorafenib) and 91% (gefitinib). These best performing pathway‐extended models demonstrated improved balance predicting both sensitive and resistant patient categories, with many of these genes having a known role in cancer aetiology. Ensemble machine learning‐based averaging of multiple pathway‐extended models derived for an individual drug increased accuracy to >70% for erlotinib, gefitinib, lapatinib and sorafenib. Through incorporation of novel cancer biomarkers, machine learning‐based pathway‐extended signatures display strong efficacy predicting both sensitive and resistant patient responses to chemotherapy.

A Review on the General Cheese Processing Technology, Flavor Biochemical Pathways and the Influence of Yeasts in Cheese

Cheese has a long history and this naturally fermented dairy product contains a range of distinctive flavors. Microorganisms in variety cheeses are an essential component and play important roles during both cheese production and ripening. However, cheeses from different countries are still handmade, the processing technology is diverse, the microbial community structure is complex and the cheese flavor fluctuates greatly. Therefore, studying the general processing technology and relationship between microbial structure and flavor formation in cheese is the key to solving the unstable quality and standardized production of cheese flavor on basis of maintaining the flavor of cheese. This paper reviews the research progress on the general processing technology and key control points of natural cheese, the biochemical pathways for production of flavor compounds in cheeses, the diversity and the role of yeasts in cheese. Combined with the development of modern detection technology, the evolution of microbial structure, population evolution and flavor correlation in cheese from different countries was analyzed, which is of great significance for the search for core functional yeast microorganisms and the industrialization prospect of traditional fermented cheese.

The Dynamic Responses of Oil Palm Leaf and Root Metabolome to Phosphorus Deficiency

Inorganic phosphate (Pi) starvation is an important abiotic constraint that affects plant cellular homeostasis, especially in tropical regions with high acidic soil and less solubilizable Pi. In the current work, oil palm seedlings were hydroponically maintained under optimal Pi-supply and no Pi-supply conditions for 14 days, and metabolites were measured by gas chromatography-mass spectrometry (GC-MS), from leaves and roots, after seven and 14 days of treatment, to investigate biochemical pathways in relation to P-utilizing strategy. After seven days of limited Pi, plant leaves showed increased levels of most soluble sugars, and after 14 days, the sugars' level decrease, except for erythritol, mannose, fructose, and glucose, which showed the highest levels. Rather in root samples, there were different but overlapping alterations, mainly on sugars, amino acids, and organic acids. The leaf sample was shown to have the highest response of sugars with myo-inositol playing a vital role in the redistribution of sugars, while maltose levels increased, indicating active degradation of starch in the root. High levels of glycerol and stearate in both roots and leaves suggest the metabolism of storage lipids for cellular energy during Pi-deficient conditions.

Identifying the miRNA Signature Association with Aging-Related Senescence in Glioblastoma

Glioblastoma (GBM) is the most common malignant brain tumor and its malignant phenotypic characteristics are classified as grade IV tumors. Molecular interactions, such as protein–protein, protein–ncRNA, and protein–peptide interactions are crucial to transfer the signaling communications in cellular signaling pathways. Evidences suggest that signaling pathways of stem cells are also activated, which helps the propagation of GBM. Hence, it is important to identify a common signaling pathway that could be visible from multiple GBM gene expression data. microRNA signaling is considered important in GBM signaling, which needs further validation. We performed a high-throughput analysis using micro array expression profiles from 574 samples to explore the role of non-coding RNAs in the disease progression and unique signaling communication in GBM. A series of computational methods involving miRNA expression, gene ontology (GO) based gene enrichment, pathway mapping, and annotation from metabolic pathways databases, and network analysis were used for the analysis. Our study revealed the physiological roles of many known and novel miRNAs in cancer signaling, especially concerning signaling in cancer progression and proliferation. Overall, the results revealed a strong connection with stress induced senescence, significant miRNA targets for cell cycle arrest, and many common signaling pathways to GBM in the network.

The interplay of spatial organization and biochemistry in building blocks of cellular signalling pathways

Biochemical pathways and networks are central to cellular information processing. While a broad range of studies have dissected multiple aspects of information processing in biochemical pathways, the effect of spatial organization remains much less understood. It is clear that space is central to intracellular organization, plays important roles in cellular information processing and has been exploited in evolution; additionally, it is being increasingly exploited in synthetic biology through the development of artificial compartments, in a variety of ways. In this paper, we dissect different aspects of the interplay between spatial organization and biochemical pathways, by focusing on basic building blocks of these pathways: covalent modification cycles and two-component systems, with enzymes which may be monofunctional or bifunctional. Our analysis of spatial organization is performed by examining a range of 'spatial designs': patterns of localization or non-localization of enzymes/substrates, theoretically and computationally. Using these well-characterized in silico systems, we analyse the following. (i) The effect of different types of spatial organization on the overall kinetics of modification, and the role of distinct modification mechanisms therein. (ii) How different information processing characteristics seen experimentally and studied from the viewpoint of kinetics are perturbed, or generated. (iii) How the activity of enzymes (bifunctional enzymes in particular) may be spatially manipulated, and the relationship between localization and activity. (iv) How transitions in spatial organization (encountered either through evolution or through the lifetime of cells, as seen in multiple model organisms) impacts the kinetic module (and pathway) behaviour, and how transitions in chemistry may be impacted by prior spatial organization. The basic insights which emerge are central to understanding the role of spatial organization in biochemical pathways in both bacteria and eukaryotes, and are of direct relevance to engineering spatial organization of pathways in bottom-up synthetic biology in cellular and cell-free systems.

Systems Biology Understanding of the Effects of Lithium on Cancer

Lithium has many widely varying biochemical and phenomenological effects, suggesting that a systems biology approach is required to understand its action. Multiple lines of evidence point to lithium as a significant factor in development of cancer, showing that understanding lithium action is of high importance. In this paper we undertake first steps toward a systems approach by analyzing mutual enrichment between the interactomes of lithium-sensitive enzymes and the pathways associated with cancer. This work integrates information from two important databases, STRING, and KEGG pathways. We find that for the majority of cancer pathways the mutual enrichment is statistically highly significant, reinforcing previous lines of evidence that lithium is an important influence on cancer.

Systems Biology Understanding of the Effects of Lithium on Affective and Neurodegenerative Disorders

Lithium has many widely varying biochemical and phenomenological effects, suggesting that a systems biology approach is required to understand its action. Multiple lines of evidence point to lithium intake and consequent blood levels as important determinants of incidence of neurodegenerative disease, showing that understanding lithium action is of high importance. In this paper we undertake first steps toward a systems approach by analyzing mutual enrichment between the interactomes of lithium-sensitive enzymes and the pathways associated with affective and neurodegenerative disorders. This work integrates information from two important databases, STRING and KEGG pathways. We find that for the majority of neurodegenerative disorders the mutual enrichment is many times greater than chance, reinforcing previous lines of evidence that lithium is an important influence on incidence of neurodegeneration. Our work suggests rational prioritization for which disorders are likely to be most sensitive to lithium and identifies genes that are likely to be useful targets for therapy adjunct to lithium.

Herbal Remedies: A Boon for Diabetic Neuropathy

Diabetic neuropathy is a chronic complication of diabetes mellitus affecting about 50% of patients. Its symptoms include decreased motility and severe pain in peripheral parts. The pathogenesis involved is an abnormality in blood vessels that supply the peripheral nerves, metabolic disorders such as myo-inositol depletion, and increased nonenzymatic glycation. Moreover, oxidative stress in neurons results in activation of multiple biochemical pathways, which results in the generation of free radicals. Apart from available marketed formulations, extensive research is being carried out on herbal-based natural products to control hyperglycemia and its associated complications. This review is focused to provide a summary on diabetic neuropathy covering its etiology, types, and existing work on herbal-based therapies, which include pure compounds isolated from plant materials, plant extracts, and Ayurvedic preparations.

Deciphering drought-induced metabolic responses and regulation in developing maize kernels

Drought stress conditions decrease maize growth and yield, and aggravate preharvest aflatoxin contamination. While several studies have been performed on mature kernels responding to drought stress, the metabolic profiles of developing kernels are not as well characterized, particularly in germplasm with contrasting resistance to both drought and mycotoxin contamination. Here, following screening for drought tolerance, a drought-sensitive line, B73, and a drought-tolerant line, Lo964, were selected and stressed beginning at 14 days after pollination. Developing kernels were sampled 7 and 14 days after drought induction (DAI) from both stressed and irrigated plants. Comparative biochemical and metabolomic analyses profiled 409 differentially accumulated metabolites. Multivariate statistics and pathway analyses showed that drought stress induced an accumulation of simple sugars and polyunsaturated fatty acids and a decrease in amines, polyamines and dipeptides in B73. Conversely, sphingolipid, sterol, phenylpropanoid and dipeptide metabolites accumulated in Lo964 under drought stress. Drought stress also resulted in the greater accumulation of reactive oxygen species (ROS) and aflatoxin in kernels of B73 in comparison with Lo964 implying a correlation in their production. Overall, field drought treatments disordered a cascade of normal metabolic programming during development of maize kernels and subsequently caused oxidative stress. The glutathione and urea cycles along with the metabolism of carbohydrates and lipids for osmoprotection, membrane maintenance and antioxidant protection were central among the drought stress responses observed in developing kernels. These results also provide novel targets to enhance host drought tolerance and disease resistance through the use of biotechnologies such as transgenics and genome editing.

Chronic Social Stress Time-Dependently Affects Neuropathic Pain-Related Cold Allodynia and Leads to Altered Expression of Spinal Biochemical Mediators

Clinical data have shown that chronic exposure to stress may be accompanied by an enhancement of inflammation-related pain sensitivity. In this context, little is however known on the impact of stress on neuropathic pain. In the present study we addressed this issue by combining the chronic constriction injury (CCI) model with an ongoing social stress (OSS) paradigm. Cold plate and von Frey tests were performed in 48 rats divided into four groups: OSS exposed to OSS, CCI subjected to chronic nerve constriction, OSS+CCI with a combination of neuropathy and stress and CON, a control group lacking any manipulation. While we did not observe any stress-related differences in mechanical sensitivity throughout the observation period, CCI rats were more sensitive to cold stimulation than OSS+CCI in the initial phase of neuropathy. A switch was observed at a later stage, leading to a hypersensitivity of the OSS+CCI compared to the CCI rats. At this time point we investigated the spinal mRNA expression of neuron and glia related molecules potentially involved in neuropathic pain and stress. The combination of psychosocial stress and neuropathic pain seemed to enhance glial cell activation, pro-inflammatory cytokine and neurotrophic factor mRNA levels, rather than glutamatergic transmission. Our data show that long lasting social stress may lead to time-dependent alteration of neuropathy-related cold pain sensitivity while mechanically-induced pain remains unchanged.

Nrf2-related gene expression and exposure to traffic-related air pollution in elderly subjects with cardiovascular disease: An exploratory panel study

Gene expression changes are linked to air pollutant exposures in in vitro and animal experiments. However, limited data are available on how these outcomes relate to ambient air pollutant exposures in humans. We performed an exploratory analysis testing whether gene expression levels were associated with air pollution exposures in a Los Angeles area cohort of elderly subjects with coronary artery disease. Candidate genes (35) were selected from published studies of gene expression-pollutant associations. Expression levels were measured weekly in 43 subjects (≤ 12 weeks) using quantitative PCR. Exposures included gaseous pollutants O3, nitrogen oxides (NOx), and CO; particulate matter (PM) pollutants elemental and black carbon (EC, BC); and size-fractionated PM mass. We measured organic compounds from PM filter extracts, including polycyclic aromatic hydrocarbons (PAHs), and determined the in vitro oxidative potential of particle extracts. Associations between exposures and gene expression levels were analyzed using mixed-effects regression models. We found positive associations of traffic-related pollutants (EC, BC, primary organic carbon, PM 0.25-2.5 PAH and/or PM 0.25 PAH, and NOx) with NFE2L2, Nrf2-mediated genes (HMOX1, NQO1, and SOD2), CYP1B1, IL1B, and SELP. Findings suggest that NFE2L2 gene expression links associations of traffic-related air pollution with phase I and II enzyme genes at the promoter transcription level.

Analysis of Five Gene Sets in Chimpanzees Suggests Decoupling between the Action of Selection on Protein-Coding and on Noncoding Elements

We set out to investigate potential differences and similarities between the selective forces acting upon the coding and noncoding regions of five different sets of genes defined according to functional and evolutionary criteria: 1) two reference gene sets presenting accelerated and slow rates of protein evolution (the Complement and Actin pathways); 2) a set of genes with evidence of accelerated evolution in at least one of their introns; and 3) two gene sets related to neurological function (Parkinson’s and Alzheimer’s diseases). To that effect, we combine human–chimpanzee divergence patterns with polymorphism data obtained from target resequencing 20 central chimpanzees, our closest relatives with largest long-term effective population size. By using the distribution of fitness effect-alpha extension of the McDonald–Kreitman test, we reproduce inferences of rates of evolution previously based only on divergence data on both coding and intronic sequences and also obtain inferences for other classes of genomic elements (untranslated regions, promoters, and conserved noncoding sequences). Our results suggest that 1) the distribution of fitness effect-alpha method successfully helps distinguishing different scenarios of accelerated divergence (adaptation or relaxed selective constraints) and 2) the adaptive history of coding and noncoding sequences within the gene sets analyzed is decoupled.

Involvement of glycolysis/gluconeogenesis and signaling regulatory pathways in Saccharomyces cerevisiae biofilms during fermentation

Compared to free (free-living) cells, biofilm cells show increased resistance and stability to high-pressure fermentation conditions, although the reasons underlying these phenomena remain unclear. Here, we investigated biofilm formation with immobilized Saccharomyces cerevisiae cells grown on fiber surfaces during the process of ethanol fermentation. The development of biofilm colonies was visualized by fluorescent labeling and confocal microscopy. RNA from yeast cells at three different biofilm development periods was extracted and sequenced by high-throughput sequencing. We quantitated gene expression differences between biofilm cells and free cells and found that 2098, 1556, and 927 genes were significantly differentially expressed, respectively. We also validated the expression of previously reported genes and identified novel genes and pathways under the control of this system. Statistical analysis revealed that biofilm genes show significant gene expression changes principally in the initial period of biofilm formation compared to later periods. Carbohydrate metabolism, amino acid metabolism, signal transduction, and oxidoreductase activity were needed for biofilm formation. In contrast to previous findings, we observed some differential expression performances of FLO family genes, indicating that cell aggregation in our immobilized fermentation system was possibly independent of flocculation. Cyclic AMP-protein kinase A and mitogen-activated protein kinase pathways regulated signal transduction pathways during yeast biofilm formation. We found that carbohydrate metabolism, especially glycolysis/gluconeogenesis, played a key role in the development of S. cerevisiae biofilms. This work provides an important dataset for future studies aimed at gaining insight into the regulatory mechanisms of immobilized cells in biofilms, as well as for optimizing bioprocessing applications with S. cerevisiae.

Cellular targets for improved manufacturing of virus-based biopharmaceuticals in animal cells

The past decade witnessed the entry into the market of new virus-based biopharmaceuticals produced in animal cells such as oncolytic vectors, virus-like particle vaccines, and gene transfer vectors. Therefore, increased attention and investment to optimize cell culture processes towards enhanced manufacturing of these bioproducts is anticipated. Herein, we review key findings on virus-host interactions that have been explored in cell culture optimization. Approaches supporting improved productivity or quality of vector preparations are discussed, mainly focusing on medium design and genetic manipulation. This review provides an integrated outline for current and future efforts in exploring cellular targets for the optimization of cell culture manufacturing of virus-based biopharmaceuticals.

[The cancer tumor: a metabolic parasite?]

Cancer cells activate glycolysis, glutaminolysis and β-oxidation to promote their biosynthesis. The low activity of pyruvate kinase, reexpressed in its embryonic isoform PKM2, generates a bottleneck at the end of glycolysis, which reorients glucose catabolism towards formation of molecules implied in numerous synthesis: ribose for nucleic acids, glycerol for lipid synthesis, etc. However, a part of glucose is transformed in pyruvate, which also comes from aminoacids catabolism. Due to the inhibition of pyruvate dehydrogenase, pyruvate is preferentially transformed into lactate, either in the presence of oxygen (Warburg effect). Lactate dehydrogenase reaction furnishes lactic acid, which acidifies the tumoral microenvironment, a process which favors the cellular growth and regenerates NAD(+), a crucial cofactor for the functioning of various metabolic pathways (glycolysis, DNA synthesis and repair…). Cancer cells consume a lot of glutamine, which replenish Krebs cycle (coupled with ATP production), and/or furnishes aspartate for nucleotides synthesis. This particular metabolism is sustained by activation of oncogenes (Myc, AKT, etc.) and suppressors inactivation (P53, PTEN…). Like a parasite, cells draw on reserves of the host to supply their own biosynthesis, while they secrete waste products (NO, polyamines, ammonia, lactate…) that promote cellular growth. A "symbiotic" cooperation could be established between tumor cells themselves, and/or with environmental cells, to maximize ATP production in relation with resources and oxygen concentration.

Biochemistry of microbial itaconic acid production

Itaconic acid is an unsaturated dicarbonic acid which has a high potential as a biochemical building block, because it can be used as a monomer for the production of a plethora of products including resins, plastics, paints, and synthetic fibers. Some Aspergillus species, like A. itaconicus and A. terreus, show the ability to synthesize this organic acid and A. terreus can secrete significant amounts to the media (>80 g/L). However, compared with the citric acid production process (titers >200 g/L) the achieved titers are still low and the overall process is expensive because purified substrates are required for optimal productivity. Itaconate is formed by the enzymatic activity of a cis-aconitate decarboxylase (CadA) encoded by the cadA gene in A. terreus. Cloning of the cadA gene into the citric acid producing fungus A. niger showed that it is possible to produce itaconic acid also in a different host organism. This review will describe the current status and recent advances in the understanding of the molecular processes leading to the biotechnological production of itaconic acid.

A board game to assist pharmacy students in learning metabolic pathways

OBJECTIVES

To develop and evaluate a board game designed to increase students' enjoyment of learning metabolic pathways; their familiarity with pathway reactions, intermediates, and regulation; and, their understanding of how pathways relate to one another and to selected biological conditions.

DESIGN

The board game, entitled Race to Glucose, was created as a team activity for first-year pharmacy students in the biochemistry curriculum.

ASSESSMENT

A majority of respondents agreed that the game was helpful for learning regulation, intermediates, and interpathway relationships but not for learning reactions, formation of energetic molecules, or relationships, to biological conditions. There was a significant increase in students' scores on game-related examination questions (68.8% pretest vs. 81.3% posttest), but the improvement was no greater than that for examination questions not related to the game (12.5% vs. 10.9%).

CONCLUSION

First-year pharmacy students considered Race to Glucose to be an enjoyable and helpful tool for learning intermediates, regulation, and interpathway relationships.