Shared and unique transcriptomic signature genes and pathways among biopsy, peripheral blood mononuclear cells and bronchoalveolar lavage samples in IPF patients revealed using comparative meta-transcriptome analysis.

Introduction: Idiopathic pulmonary fibrosis (IPF) affects the tissue surrounding the alveoli and occurs when the lung tissue becomes thick and stiff for unknown reasons. Clinical findings are fairly well settled, but the molecular mechanisms of IPF are still poorly known. Materials and Methods: To further our understanding, we collected publicly available transcriptome dataset from IPF cohorts, grouped them according to sampling method [bronchoalveolar lavage (BAL), biopsy, blood], and performed comparative meta-transcriptome study to (I) unravel key pathways (II), set out differences in discovered genes, pathways, and functional annotation with respect to the sampling method, and (III) find biomarkers for early diagnosis. Result: The resulting lists are also compared with DisGeNet reported genes, earlier work, and Kyoto encyclopedia of genes and genomes (KEGG) pathways. Several pathways are shared among BAL and biopsy samples while blood samples point to alternative pathways, indicating the noise in information obtained from these samples. Conclusions: Common to all sampling methods, interleukin-10 pathway and extracellular signaling pathways are pointed as further targets.

Species-level identification of enterotype-specific microbial markers for colorectal cancer and adenoma.

Enterotypes have been shown to be an important factor for population stratification based on gut microbiota composition, leading to a better understanding of human health and disease states. Classifications based on compositional patterns will have implications for personalized microbiota-based solutions. There have been limited enterotype based studies on colorectal adenoma and cancer. Here, an enterotype-based meta-analysis of fecal shotgun metagenomic studies was performed, including 1579 samples of healthy controls (CTR), colorectal adenoma (ADN) and colorectal cancer (CRC) in total. Gut microbiota of healthy people were clustered into three enterotypes (Ruminococcus-, Bacteroides- and Prevotella-dominated enterotypes). Reference-based enterotype assignments were performed for CRC and ADN samples, using the supervised machine learning algorithm, K-nearest neighbors. Differential abundance analyses and random forest classification were conducted on each enterotype between healthy controls and CRC-ADN groups, revealing novel enterotype-specific microbial markers for non-invasive CRC screening strategies. Furthermore, we identified microbial species unique to each enterotype that play a role in the production of secondary bile acids and short-chain fatty acids, unveiling the correlation between cancer-associated gut microbes and dietary patterns. The enterotype-based approach in this study is promising in elucidating the mechanisms of differential gut microbiome profiles, thereby improving the efficacy of personalized microbiota-based solutions.

Identification of Reference Genes in Chordoma Cells Allows Cross-Comparison of Expression Studies Across Subtypes.

AIM: To present the best housekeeping genes including clival/sacral based chordoma, and the nucleus pulposus cells. MATERIAL AND METHODS: We investigated 13 candidate reference genes in public chordoma array transcriptome datasets, validated these genes by using RT-PCR, and evaluated their stability with NormFinder, geNorm, and Bestkeeper. RESULTS: YWHAZ, TBP and PGK1 genes were identified as the most stable reference genes as confirmed with three different approaches. Conversely, KRT8, KRT19 and GAPDH genes are less stable and not appropriate for use in chordoma research. CONCLUSION: For normalization of RT-PCR experiments in gene profiling of chordoma, we recommend the use of the stable genes YWHAZ, TBP and PGK1.

UV and chemically induced Halomonas smyrnensis mutants for enhanced levan productivity.

Halomonas smyrnensis AAD6T is a moderately halophilic bacterium proven to be a powerful biotechnological tool with its ability to accumulate valuable biopolymers such as levan and poly(3-hydroxybutyrate) (PHB). Levan is a fructose homopolymer with ß-2,6 fructofuranosidic linkages on the polymer backbone, and its distinctive applications in various industries such as food, pharmaceutical, medical, and chemical have been well-defined. On the other hand, PHB is a promising raw material to produce biodegradable plastics. Although it was shown in our previous studies that H. smyrnensis AAD6T exhibits one of the highest conversion yields of sucrose to levan reported to date, novel strategies are required to overcome high costs of levan production. In this study, we aimed at increasing levan productivity of H. smyrnensis AAD6T cultures using random mutagenesis techniques combined (i.e., ethyl methanesulfate treatment and/or ultraviolet irradiation). After several consecutive treatments, mutant strains BAE2, BAE5 and BAE6 were selected as efficient levan producers, as BAE2 standing out as the most efficient one not only in sucrose utilization and levan production rates, but also in final PHB concentrations. The mutants' whole genome sequences were analysed to determine the mutations occurred. Several mutations in genes related to central carbon metabolism and osmoregulation were found. Our results suggest that random mutagenesis can be a facile and efficient strategy to enhance the performance of extremophiles in adverse conditions.

Prevalence and clinical/molecular characteristics of PTEN mutations in Turkish children with autism spectrum disorders and macrocephaly.

BACKGROUND: Phosphatase and tensin homolog (PTEN) germline mutations are associated with cancer syndromes (PTEN hamartoma tumor syndrome; PHTS) and in pediatric patients with autism spectrum disorder (ASD) and macrocephaly. The exact prevalence of PTEN mutations in patients with ASD and macrocephaly is uncertain; with prevalence rates ranging from 1% to 17%. Most studies are retrospective and contain more adult than pediatric patients, there is a need for more prospective pediatric studies. METHODS: We recruited 131 patients (108 males, 23 females) with ASD and macrocephaly between the ages of 3 and 18 from five child and adolescent psychiatry clinics in Turkey from July 2018 to December 2019. We defined macrocephaly as occipito-frontal HC size at or greater than 2 standard deviations (SD) above the mean for age and sex on standard growth charts. PTEN gene sequence analysis was performed using a MiSeq next generation sequencing (NGS) platform, (Illumina). CONCLUSION: PTEN gene sequence analyses identified three pathogenic/likely pathogenic mutations [NM_000314.6; p.(Pro204Leu), (p.Arg233*) and novel (p.Tyr176Cys*8)] and two variants of uncertain significance (VUS) [NM_000314.6; p.(Ala79Thr) and c.*10del]. We also report that patient with (p.Tyr176Cys*8) mutation has Grade 1 hepatosteatosis, a phenotype not previously described. This is the first PTEN prevalence study of patients with ASD and macrocephaly in Turkey and South Eastern Europe region with a largest homogenous cohort. The prevalence of PTEN mutations was found 3.8% (VUS included) or 2.29% (VUS omitted). We recommend testing for PTEN mutations in all patients with ASD and macrocephaly.

High level production of itaconic acid at low pH by Ustilago maydis with fed-batch fermentation.

The metabolically engineered plant pathogen Ustilago maydis MB215 Δcyp3 Petefria1 has been cultivated to produce more than 80 g/L itaconate in 16 L scale pH and temperature controlled fermentation, in fed-batch mode with two successive feedings. The effect of pH as well as successive rounds of feeding has been quantified via elemental balances. Volumetric itaconic acid productivity gradually decreased with successive glucose feedings with increasing itaconic titers, with nearly constant product yield. Extracellular pH was decreased from 6 down to 3.5 and the fermentation was characterized in specific uptake, production, and growth rates. Notable is that the biomass composition changes significantly from growth phase to itaconic acid production phase, carbon content increases from 42% to around 62%. Despite the gradual decrease in itaconic acid levels with decreasing pH (nearly 50% decrease in itaconic acid at pH 3.5, compared to pH 6), significant itaconate production is still observed at pH 4 (around 63 g/L). Biomass yield remained nearly constant until pH 4. Taken together, these results strongly illustrate the potential of engineered Ustilago maydis in itaconate production at commercial levels.

Black-box kinetic modeling of growth and citric acid production and estimation of ATP maintenance parameters for Candida oleophila ATCC20177.

Mathematical modeling represents and predicts biological systems, explains underlying mechanisms, constituting one of the key focus points for fundamental and applied research to improve our understanding and to decrease costs. Organic acids are used in several industries such as monomers for bioplastics, food preservatives and additives, pharmaceuticals, and agriculture. Nonpetrochemical, sustainable production of organic acids is therefore of great interest. An important step in production of organic acids is the determination of growth and acid production dynamics, as the product itself may have direct and indirect inhibitory effects on the host's metabolism. The aim of this study it twofold: (i) to determine the parameters related to energetics of growth and production as growth ( K x ) and nongrowth associated (mATP ) maintenance constants and (ii) to set up and analyze an unstructured, black-box kinetic model to describe the dynamics of the growth and production of citric acid by Candida oleophila ATCC20177 using published batch fermentation data. K x and mATP were found to be 2.3 ± 1.7 and 5.25 ± 2.75, respectively, for the published P/O ratio of 1.45. The parameter sensitivities and correlations are determined using the Monte Carlo approach, and the final model is tested using chemostat data.

Dynamic co-culture metabolic models reveal the fermentation dynamics, metabolic capacities and interplays of cheese starter cultures.

In this study, we have investigated the cheese starter culture as a microbial community through a question: can the metabolic behaviour of a co-culture be explained by the characterized individual organism that constituted the co-culture? To address this question, the dairy-origin lactic acid bacteria Lactococcus lactis subsp. cremoris, Lactococcus lactis subsp. lactis, Streptococcus thermophilus and Leuconostoc mesenteroides, commonly used in cheese starter cultures, were grown in pure and four different co-cultures. We used a dynamic metabolic modelling approach based on the integration of the genome-scale metabolic networks of the involved organisms to simulate the co-cultures. The strain-specific kinetic parameters of dynamic models were estimated using the pure culture experiments and they were subsequently applied to co-culture models. Biomass, carbon source, lactic acid and most of the amino acid concentration profiles simulated by the co-culture models fit closely to the experimental results and the co-culture models explained the mechanisms behind the dynamic microbial abundance. We then applied the co-culture models to estimate further information on the co-cultures that could not be obtained by the experimental method used. This includes estimation of the profile of various metabolites in the co-culture medium such as flavour compounds produced and the individual organism level metabolic exchange flux profiles, which revealed the potential metabolic interactions between organisms in the co-cultures.

Association of 5'UTR polymorphism of secretory phospholipase A2 group IIA (PLA2G2A) gene with prostate cancer metastasis.

Phospholipase A2 (PLA2) enzymes are small lipolytic hydrolases that can regulate immune responses through generation of Arachidonic Acid (AA), a precursor molecule of lipid mediators like prostaglandins, leukotrienes and thromboxanes. One of the family members of PLA2, secretory Phospholipase A2 Group IIA (PLA2G2A), was associated with different types of malignancies including prostate cancer. Elevated serum levels of PLA2G2A was found in prostate cancer (PCa) patients and associated with increased tumor grade in literature. 5'UTR regions have regulatory role in protein expression by controlling the accessibility of factors necessary for the translation initiation. Single nucleotide polymorphisms at 5'UTR regions have the potential to affect mRNA translation efficiency resulting in altered protein levels depending on structure and nucleotide content. Given that the 5'UTR polymorphism in PLA2G2A gene (rs11573156) is associated with increased serum levels of PLA2G2A, the association of this 5'UTR polymorphism with PCa susceptibility and metastasis was investigated in this study. Total of 261 PCa patients and 128 control individuals were genotyped with polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Individuals with heterozygous CG genotype was found to have significantly reduced risk of PCa metastasis with an Odds Ratio (OR) of 0.405 (p = 0.028, 95%CI = 0.181-0.906), compared to the carriers of homozygous CC genotype (p > 0.05) suggesting an anti-metastatic effect for the G allele. No association was found between PCa susceptibility and Gleason score (p > 0.05) in Turkish population.

Genome-Scale Metabolic Model of a Microbial Cell Factory (Brevibacillus thermoruber 423) with Multi-Industry Potentials for Exopolysaccharide Production.

Brevibacillus thermoruber 423 is a thermophilic bacterium capable of producing high levels of exopolysaccharide (EPS) that has broad applications in nutrition, feed, cosmetics, pharmaceutical, and chemical industries, not to mention in health and bionanotechnology sectors. EPS is a natural, nontoxic, and biodegradable polymer of sugar residues and plays pivotal roles in cell-to-cell interactions, adhesion, biofilm formation, and protection of cell against environmental extremes. This bacterium is a thermophilic EPS producer while exceeding other thermophilic producers by virtue of high level of polymer synthesis. Recently, B. thermoruber 423 was noted for relevance to multiple industry sectors because of its capacity to use xylose, and produce EPS, isoprenoids, ethanol/butanol, lipases, proteases, cellulase, and glucoamylase enzymes as well as its resistance to arsenic. A key step in understanding EPS production with a systems-based approach is the knowledge of microbial genome sequence. To speed biotechnology and industrial applications, this study reports on a genome-scale metabolic model (GSMM) of B. thermoruber 423, constructed using the recently available high-quality genome sequence that we have subsequently validated using physiological data on batch growth and EPS production on seven different carbon sources. The model developed contains 1454 reactions (of which 1127 are assigned an enzyme commission number) and 1410 metabolites from 925 genes. This GSMM offers the promise to enable and accelerate further systems biology and industrial scale studies, not to mention the ability to calculate metabolic flux distribution in large networks and multiomic data integration.

A genome-scale metabolic network of the aroma bacterium Leuconostoc mesenteroides subsp. cremoris.

Leuconostoc mesenteroides subsp. cremoris is an obligate heterolactic fermentative lactic acid bacterium that is mostly used in industrial dairy fermentations. The phosphoketolase pathway (PKP) is a unique feature of the obligate heterolactic fermentation, which leads to the production of lactate, ethanol, and/or acetate, and the final product profile of PKP highly depends on the energetics and redox state of the organism. Another characteristic of the L. mesenteroides subsp. cremoris is the production of aroma compounds in dairy fermentation, such as in cheese production, through the utilization of citrate. Considering its importance in dairy fermentation, a detailed metabolic characterization of the organism is necessary for its more efficient use in the industry. To this aim, a genome-scale metabolic model of dairy-origin L. mesenteroides subsp. cremoris ATCC 19254 (iLM.c559) was reconstructed to explain the energetics and redox state mechanisms of the organism in full detail. The model includes 559 genes governing 1088 reactions between 1129 metabolites, and the reactions cover citrate utilization and citrate-related flavor metabolism. The model was validated by simulating co-metabolism of glucose and citrate and comparing the in silico results to our experimental results. Model simulations further showed that, in co-metabolism of citrate and glucose, no flavor compounds were produced when citrate could stimulate the formation of biomass. Significant amounts of flavor metabolites (e.g., diacetyl and acetoin) were only produced when citrate could not enhance growth, which suggests that flavor formation only occurs under carbon and ATP excess. The effects of aerobic conditions and different carbon sources on product profiles and growth were also investigated using the reconstructed model. The analyses provided further insights for the growth stimulation and flavor formation mechanisms of the organism.

Comparative differences between T1a/b and T1e/m as substages in T1 urothelial carcinoma of the bladder

ABSTRACT Objective To evaluate the prognostic value of the depth of lamina propria invasion in patients with T1 bladder cancer and to display comparative differences between the T1a/b and T1e/m substaging systems. Patients and Methods This study included 106 patients with primary stage T1 urothelial bladder tumours who underwent surgery between January 2009 and December 2014. Pathologic specimens were re-evaluated to confirm the diagnosis of T1 and substaging by the same pathologist using two systems: T1a and T1b, and T1m and T1e. Age, tumour size, multiplicity, associated carcinoma in situ, tumour grade, and T1 substaging system were investigated to detect the relation between disease progression and recurrence. Results The recurrence rate was 52% for T1a (n=42) vs. 76% for T1b (n=20) (p=0.028) and 55% for T1m (n=32) vs. 62% for T1e (n=30), respectively (p=0.446). There was no significant difference between the substaging groups for disease progression: T1a (n=12, 15%) vs. T1b (n=7, 27%), and T1m (n=8, 13.8%) vs. T1e (n=11, 23%) (p>0.05). In the multivariate analysis, tumour size >3 cm (p=0.008), multiplicity (p=0.049), and substaging T1b (p=0.043) were independent predictive factors for tumour recurrence. According to the Kaplan-Meier actuarial method, recurrence-free survival was significantly different in patients with pT1a tumours compared with those with pT1b tumours (p=0.033). Conclusions Substaging T1 provides a prediction of disease recurrence. Regarding recurrence, T1a/b substaging can provide better knowledge of disease behaviour because it is predicted as more superior than T1 m/e, and it can help in determining the requirement for early cystectomy.

Comparative differences between T1a/b and T1e/m as substages in T1 urothelial carcinoma of the bladder.

OBJECTIVE: To evaluate the prognostic value of the depth of lamina propria invasion in patients with T1 bladder cancer and to display comparative differences between the T1a/b and T1e/m substaging systems. PATIENTS AND METHODS: This study included 106 patients with primary stage T1 urothelial bladder tumours who underwent surgery between January 2009 and December 2014. Pathologic specimens were re-evaluated to confirm the diagnosis of T1 and substaging by the same pathologist using two systems: T1a and T1b, and T1m and T1e. Age, tumour size, multiplicity, associated carcinoma in situ, tumour grade, and T1 substaging system were investigated to detect the relation between disease progression and recurrence. RESULTS: The recurrence rate was 52% for T1a (n=42) vs. 76% for T1b (n=20) (p=0.028) and 55% for T1m (n=32) vs. 62% for T1e (n=30), respectively (p=0.446). There was no significant difference between the substaging groups for disease progression: T1a (n=12, 15%) vs. T1b (n=7, 27%), and T1m (n=8, 13.8%) vs. T1e (n=11, 23%) (p>0.05). In the multivariate analysis, tumour size >3 cm (p=0.008), multiplicity (p=0.049), and substaging T1b (p=0.043) were independent predictive factors for tumour recurrence. According to the Kaplan-Meier actuarial method, recurrence-free survival was significantly different in patients with pT1a tumours compared with those with pT1b tumours (p=0.033). CONCLUSIONS: Substaging T1 provides a prediction of disease recurrence. Regarding recurrence, T1a/b substaging can provide better knowledge of disease behaviour because it is predicted as more superior than T1 m/e, and it can help in determining the requirement for early cystectomy.

Draft Genome Sequence of Magnesium-Dissolving Lactococcus garvieae A1, Isolated from Soil.

The probiotic bacterium Lactococcus garvieae A1, isolated from soil, is interesting for biomining applications. Here, we report the draft genome sequence and annotation of this strain, with a focus on metal transporter enzymes.

A new hope for obesity management: Boron inhibits adipogenesis in progenitor cells through the Wnt/ß-catenin pathway.

Obesity is a worldwide medical problem resulting in serious morbidity and mortality involving differentiation of pre-adipocytes into mature adipocytes (adipogenesis). Boron treatment has been reported to be associated with weight reduction in experimental animals; however, its effects on pre-adipocyte differentiation and anti-adipogenic molecular mechanisms are unknown. In this study, we demonstrate the inhibitory activities of boric acid (BA) and sodium pentaborate pentahydrate (NaB) on adipogenesis using common cellular models. Boron treatment repressed the expression of adipogenesis-related genes and proteins, including CCAAT-enhancer-binding protein α and peroxisome proliferator-activated receptor γ, by regulating critical growth factors and the ß-catenin, AKT, and extracellular signal-regulated kinase signaling pathways. In addition, although boron treatment did not induce apoptosis in pre-adipocytes, it depressed mitotic clonal expansion by regulation of cell cycle genes. Overall, these data offer promising insights into the prevention/treatment of obesity and associated diseases.

How biochemical constraints of cellular growth shape evolutionary adaptations in metabolism.

Evolutionary adaptations in metabolic networks are fundamental to evolution of microbial growth. Studies on unneeded-protein synthesis indicate reductions in fitness upon nonfunctional protein synthesis, showing that cell growth is limited by constraints acting on cellular protein content. Here, we present a theory for optimal metabolic enzyme activity when cells are selected for maximal growth rate given such growth-limiting biochemical constraints. We show how optimal enzyme levels can be understood to result from an enzyme benefit minus cost optimization. The constraints we consider originate from different biochemical aspects of microbial growth, such as competition for limiting amounts of ribosomes or RNA polymerases, or limitations in available energy. Enzyme benefit is related to its kinetics and its importance for fitness, while enzyme cost expresses to what extent resource consumption reduces fitness through constraint-induced reductions of other enzyme levels. A metabolic fitness landscape is introduced to define the fitness potential of an enzyme. This concept is related to the selection coefficient of the enzyme and can be expressed in terms of its fitness benefit and cost.

Understanding regulation of metabolism through feasibility analysis.

Understanding cellular regulation of metabolism is a major challenge in systems biology. Thus far, the main assumption was that enzyme levels are key regulators in metabolic networks. However, regulation analysis recently showed that metabolism is rarely controlled via enzyme levels only, but through non-obvious combinations of hierarchical (gene and enzyme levels) and metabolic regulation (mass action and allosteric interaction). Quantitative analyses relating changes in metabolic fluxes to changes in transcript or protein levels have revealed a remarkable lack of understanding of the regulation of these networks. We study metabolic regulation via feasibility analysis (FA). Inspired by the constraint-based approach of Flux Balance Analysis, FA incorporates a model describing kinetic interactions between molecules. We enlarge the portfolio of objectives for the cell by defining three main physiologically relevant objectives for the cell: function, robustness and temporal responsiveness. We postulate that the cell assumes one or a combination of these objectives and search for enzyme levels necessary to achieve this. We call the subspace of feasible enzyme levels the feasible enzyme space. Once this space is constructed, we can study how different objectives may (if possible) be combined, or evaluate the conditions at which the cells are faced with a trade-off among those. We apply FA to the experimental scenario of long-term carbon limited chemostat cultivation of yeast cells, studying how metabolism evolves optimally. Cells employ a mixed strategy composed of increasing enzyme levels for glucose uptake and hexokinase and decreasing levels of the remaining enzymes. This trade-off renders the cells specialized in this low-carbon flux state to compete for the available glucose and get rid of over-overcapacity. Overall, we show that FA is a powerful tool for systems biologists to study regulation of metabolism, interpret experimental data and evaluate hypotheses.