The 3Ranker: An AI-based Algorithm for Finding Non-animal Alternative Methods.

The search for existing non-animal alternative methods for use in experiments is currently challenging because of the lack of both comprehensive structured databases and balanced keyword-based search strategies to mine unstructured textual databases. In this paper we describe 3Ranker, which is a fast, keyword-independent algorithm for finding non-animal alternative methods for use in biomedical research. The 3Ranker algorithm was created by using a machine learning approach, consisting of a Random Forest model built on a dataset of 35 million abstracts and constructed with weak supervision, followed by iterative model improvement with expert curated data. We found a satisfactory trade-off between sensitivity and specificity, with Area Under the Curve (AUC) values ranging from 0.85-0.95. Trials showed that the AI-based classifier was able to identify articles that describe potential alternatives to animal use, among the thousands of articles returned by generic PubMed queries on dermatitis and Parkinson's disease. Application of the classification models on time series data showed the earlier implementation and acceptance of Three Rs principles in the area of cosmetics and skin research, as compared to the area of neurodegenerative disease research. The 3Ranker algorithm is freely available at www.open3r.org; the future goal is to expand this framework to cover multiple research domains and to enable its broad use by researchers, policymakers, funders and ethical review boards, in order to promote the replacement of animal use in research wherever possible.

Nailfold capillaroscopy and candidate-biomarker levels in systemic sclerosis-associated pulmonary hypertension: A cross-sectional study.

Objectives: Pulmonary hypertension is one of the leading causes of death in systemic sclerosis. Early detection and treatment of pulmonary hypertension in systemic sclerosis is crucial. Nailfold capillaroscopy microscopy, vascular autoantibodies AT1R and ETAR, and several candidate-biomarkers have the potential to serve as noninvasive tools to identify systemic sclerosis patients at risk for developing pulmonary hypertension. Here, we explore the classifying potential of nailfold capillaroscopy microscopy characteristics and serum levels of selected candidate-biomarkers in a sample of systemic sclerosis patients with and without different forms of pulmonary hypertension. Methods: A total of 81 consecutive systemic sclerosis patients were included, 40 with systemic sclerosis pulmonary hypertension and 41 with no pulmonary hypertension. In each group, quantitative and qualitative nailfold capillaroscopy microscopy characteristics, vascular autoantibodies AT1R and ETAR, and serum levels of 24 soluble serum factors were determined. For evaluation of the nailfold capillaroscopy microscopy characteristics, linear regression analysis accounting for age, sex, and diffusing capacity of the lungs for carbon monoxide percentage predicted was used. Autoantibodies and soluble serum factor levels were compared using two-sample t test with equal variances. Results: No statistically significant differences were observed in quantitative or qualitative nailfold capillaroscopy microscopy characteristics, or vascular autoantibody ETAR and AT1R titer between systemic sclerosis-pulmonary hypertension and systemic sclerosis-no pulmonary hypertension. In contrast, several serum levels of soluble factors differed between groups: Endostatin, sVCAM, and VEGFD were increased, and CXCL4, sVEGFR2, and PDGF-AB/BB were decreased in systemic sclerosis-pulmonary hypertension. Random forest classification identified Endostatin and CXCL4 as the most predictive classifiers to distinguish systemic sclerosispulmonary hypertension from systemic sclerosis-no pulmonary hypertension. Conclusion: This study shows the potential for several soluble serum factors to distinguish systemic sclerosis-pulmonary hypertension from systemic sclerosis-no pulmonary hypertension. We found no classifying potential for qualitative or quantitative nailfold capillaroscopy microscopy characteristics, or vascular autoantibodies.

A proteomics approach to identify COPD-related changes in lung fibroblasts.

Lung fibroblasts are implicated in abnormal tissue repair in chronic obstructive pulmonary disease (COPD). The exact mechanisms are unknown and comprehensive analysis comparing COPD- and control fibroblasts is lacking. The aim of this study is to gain insight into the role of lung fibroblasts in COPD pathology using unbiased proteomic and transcriptomic analysis. Protein and RNA were isolated from cultured parenchymal lung fibroblasts of 17 patients with stage IV COPD and 16 non-COPD controls. Proteins were analyzed using LC-MS/MS and RNA through RNA sequencing. Differential protein and gene expression in COPD was assessed via linear regression, followed by pathway enrichment, correlation analysis, and immunohistological staining in lung tissue. Proteomic and transcriptomic data were compared to investigate the overlap and correlation between both levels of data. We identified 40 differentially expressed (DE) proteins and zero DE genes between COPD and control fibroblasts. The most significant DE proteins were HNRNPA2B1 and FHL1. Thirteen of the 40 proteins were previously associated with COPD, including FHL1 and GSTP1. Six of the 40 proteins were related to telomere maintenance pathways, and were positively correlated with the senescence marker LMNB1. No significant correlation between gene and protein expression was observed for the 40 proteins. We hereby describe 40 DE proteins in COPD fibroblasts including previously described COPD proteins (FHL1, GSTP1) and new COPD research targets like HNRNPA2B1. Lack of overlap and correlation between gene and protein data supports the use of unbiased proteomics analysis and indicates that different types of information are generated with both methods.

Differential Pneumococcal Growth Features in Severe Invasive Disease Manifestations.

The nasopharyngeal commensal Streptococcus pneumoniae can become invasive and cause metastatic infection. This requires the pneumococcus to have the ability to adapt, grow, and reside in diverse host environments. Therefore, we studied whether the likelihood of severe disease manifestations was related to pneumococcal growth kinetics. For 383 S. pneumoniae blood isolates and 25 experimental mutants, we observed highly reproducible growth curves in nutrient-rich medium. The derived growth features were lag time, maximum growth rate, maximum density, and stationary-phase time before lysis. First, the pathogenicity of each growth feature was probed by comparing isolates from patients with and without marked preexisting comorbidity. Then, growth features were related to the propensity of causing severe manifestations of invasive pneumococcal disease (IPD). A high maximum bacterial density was the most pronounced pathogenic growth feature, which was also an independent predictor of 30-day mortality (P = 0.03). Serotypes with an epidemiologically higher propensity for causing meningitis displayed a relatively high maximum density (P < 0.005) and a short stationary phase (P < 0.005). Correspondingly, isolates from patients diagnosed with meningitis showed an especially high maximum density and short stationary phase compared to isolates from the same serotype that had caused uncomplicated bacteremic pneumonia. In contrast, empyema-associated strains were characterized by a relatively long lag phase (P < 0.0005), and slower growth (P < 0.005). The course and dissemination of IPD may partly be attributable to the pneumococcal growth features involved. If confirmed, we should tailor the prevention and treatment strategies for the different infection sites that can complicate IPD. IMPORTANCE Streptococcus pneumoniae is a leading infectious cause of deaths worldwide. To understand the course and outcome of pneumococcal infection, most research has focused on the host and its response to contain bacterial growth. However, bacterial epidemiology suggest that certain pneumococcal serotypes are particularly prone to causing complicated infections. Therefore, we took the bacterial point of view, simply examining in vitro growth features for hundreds of pneumococcal blood isolates. Their growth curves were very reproducible. Certain poles of pneumococcal growth features were indeed associated with specific clinical manifestations like meningitis or pleural empyema. This indicates that bacterial growth style potentially affects the progression of infection. Further research on bacterial growth and adaptation to different host environments may therefore provide key insight into pathogenesis of complicated invasive disease. Such knowledge could lead to more tailored vaccine targets or therapeutic approaches to reduce the million deaths that are caused by pneumococcal disease every year.

Maternal pre-pregnancy overweight and neonatal gut bacterial colonization are associated with cognitive development and gut microbiota composition in pre-school-age offspring.

Maternal gestational obesity is a risk factor for offspring's neurodevelopment and later neuro-cognitive disorders. Altered gut microbiota composition has been found in patients with neurocognitive disorders, and in relation to maternal metabolic health. We explored the associations between gut microbiota and cognitive development during infancy, and their link with maternal obesity. In groups of children from the Pisa birth Cohort (PISAC), we analysed faecal microbiota composition by 16S rRNA marker gene sequencing of first-pass meconium samples and of faecal samples collected at age 3, 6, 12, 24, 36 months, and its relationship with maternal gestational obesity or diabetes, and with cognitive development, as measured from 6 to 60 months of age by the Griffith's Mental Development Scales. Gut microbiota composition in the first phases of life is dominated by Bifidobacteria (Actinobacteria phylum), with contribution of Escherichia/Shigella and Klebsiella genera (Proteobacteria phylum), whereas Firmicutes become more dominant at 36 months of age. Maternal overweight leads to lower abundance of Bifidobacterium, Blautia and Ruminococcus, and lower practical reasoning scores in the offspring at the age of 36 months. In the whole population, microbiota in the first-pass meconium samples shows much higher alpha diversity compared to later samples, and its composition, particularly Bifidobacterium and Veillonella abundances, correlates with practical reasoning scores at 60 months of age. Maternal overweight correlates with bacterial colonization and with the development of reasoning skills at pre-school age. Associations between neonatal gut colonization and later cognitive function provide new perspectives of primary (antenatal) prevention of neurodevelopmental disorders.

Charting host-microbe co-metabolism in skin aging and application to metagenomics data.

During aging of human skin, a number of intrinsic and extrinsic factors cause the alteration of the skin's structure, function and cutaneous physiology. Many studies have investigated the influence of the skin microbiome on these alterations, but the molecular mechanisms that dictate the interplay between these factors and the skin microbiome are still not fully understood. To obtain more insight into the connection between the skin microbiome and the human physiological processes involved in skin aging, we performed a systematic study on interconnected pathways of human and bacterial metabolic processes that are known to play a role in skin aging. The bacterial genes in these pathways were subsequently used to create Hidden Markov Models (HMMs), which were applied to screen for presence of defined functionalities in both genomic and metagenomic datasets of skin-associated bacteria. These models were further applied on 16S rRNA gene sequencing data from skin microbiota samples derived from female volunteers of two different age groups (25-28 years ('young') and 59-68 years ('old')). The results show that the main bacterial pathways associated with aging skin are those involved in the production of pigmentation intermediates, fatty acids and ceramides. This study furthermore provides evidence for a relation between skin aging and bacterial enzymes involved in protein glycation. Taken together, the results and insights described in this paper provide new leads for intervening with bacterial processes that are associated with aging of human skin.

Blood-Based Immune Profiling Combined with Machine Learning Discriminates Psoriatic Arthritis from Psoriasis Patients.

Psoriasis (Pso) is a chronic inflammatory skin disease, and up to 30% of Pso patients develop psoriatic arthritis (PsA), which can lead to irreversible joint damage. Early detection of PsA in Pso patients is crucial for timely treatment but difficult for dermatologists to implement. We, therefore, aimed to find disease-specific immune profiles, discriminating Pso from PsA patients, possibly facilitating the correct identification of Pso patients in need of referral to a rheumatology clinic. The phenotypes of peripheral blood immune cells of consecutive Pso and PsA patients were analyzed, and disease-specific immune profiles were identified via a machine learning approach. This approach resulted in a random forest classification model capable of distinguishing PsA from Pso (mean AUC = 0.95). Key PsA-classifying cell subsets selected included increased proportions of differentiated CD4+CD196+CD183-CD194+ and CD4+CD196-CD183-CD194+ T-cells and reduced proportions of CD196+ and CD197+ monocytes, memory CD4+ and CD8+ T-cell subsets and CD4+ regulatory T-cells. Within PsA, joint scores showed an association with memory CD8+CD45RA-CD197- effector T-cells and CD197+ monocytes. To conclude, through the integration of in-depth flow cytometry and machine learning, we identified an immune cell profile discriminating PsA from Pso. This immune profile may aid in timely diagnosing PsA in Pso.

High throughput screening of technological and biopreservation traits of a large set of wild lactic acid bacteria from Brazilian artisanal cheeses.

This study aimed to evaluate technological (acidification, proteolysis, lipolysis, resistance to low pH, NaCl, and bile salts) and biopreservation (antimicrobial activity against foodborne pathogens) features of 1002 LAB by high throughput screening (HTS) methods. The LAB was isolated from 11 types of Brazilian artisanal cheeses (BAC) marketed in the main 5 producing regions. Remarkable intra-species variability in acidification rates have been found, which was most pronounced between isolates from Mina's artisanal cheeses, Caipira and Coalho cheeses. Lacticaseibacillus paracasei and Levilactobacillus brevis showed the fastest acidification rate; however, all isolates showed slower acidification rates than a lactococcal control strain (4.3 × lower). When testing inhibitory effects, > 75% of LAB isolates could inhibit the growth of Staphylococcus aureus ATCC 19095 and Listeria monocytogenes ATCC 7644. Two of these isolates, identified as Lactiplantibacillus plantarum and Lentilactobacillus buchneri, the sterile and neutral supernatants alone, were sufficient to inhibit L. monocytogenes growth. Principal component analysis (PCA) allowed the identification of functional groups based on proteolytic and lipolytic activity, osmotic stress resistance, and inhibition of L. monocytogenes. The type of cheese the isolates were recovered from influenced properties such as anti-listerial compounds and lipolytic enzyme production. The use of HTS and multivariate statistics allowed insights into a diverse set of LAB technological and biopreservation properties. These findings allow a profound knowledge of the heterogeneity of a large set of isolates, which can be further used to design starter cultures with varied and combined properties, such as biopreservation and technological features. Besides that, HTS makes it possible to analyze a vast panel of LAB strains, reducing costs and time within laboratory analysis, while avoiding the loss of information once all LAB are tested at the same time (differently from the traditional labor-intensive approach, in which a few numbers of strains is tested per time).

Autoantibody profiles in systemic sclerosis; a comparison of diagnostic tests.

OBJECTIVES: Autoimmune antibody profiling plays a prominent role in both classification and prognosis of systemic sclerosis (SSc). In the last years novel autoantibodies have been discovered and have become available in diagnostic assays. However, standardization in autoimmune serology is lacking, which may have a negative impact on the added value of autoantibodies in diagnosis and prognosis of SSc. In this paper we describe the comparison of commercially available diagnostic assays for the detection of SSc-associated autoantibodies and explored the coexistence of multiple SSc-associated autoantibodies within patients. METHODS: Serum samples of 347 patients from the Nijmegen Systemic Sclerosis Cohort were included in this study. All patients fulfilled the ACR/EULAR 2013 classification criteria for SSc and were classified as DcSSc or LcSSc according to the Leroy and Medsger criteria. All samples were evaluated on standard laboratory diagnostic tests for detection of SSc-specific autoantibodies CENPA and CENPB (ACA), Scl-70 (ATA), RNA Polymerase III (rp11/155) (ARA), and SSc-associated autoantibodies Fibrillarin, Th-To, PM-scl75, PM-Scl100, RNP68/A/C, Ku, NOR90, and PDGFR from suppliers EUROIMMUN, D-tek and Thermo Fisher Scientific. RESULTS: We found that 79% of the patients was positive for one or more of the SSc autoantibodies. Overall, a high agreement was observed between the diagnostic methods for the SSC-specific autoantibodies listed in the ACR/EULAR criteria (ATA, ACA, and ARA) (Cohen's kappa 0.53-0.97). However, a lower agreement was found for SSc-associated autoantibodies PM-Scl, and Ku, as well as for the SSc-specific autoantibodies fibrillarin and Th-To. Furthermore, the data revealed that the presence of ATA, ARA and ACA is predominantly mutually exclusive, with only a fraction of the patients testing positive for both ATA and ARA. CONCLUSION: Our data showed high concordance of prevalent SSc-specific autoantibodies between different diagnostic assays. Further standardisation for low prevalent SSc-specific and SSc-associated autoantibodies is needed.

Live Biotherapeutic Products, A Road Map for Safety Assessment.

Recent developments in the understanding of the relationship between the microbiota and its host have provided evidence regarding the therapeutic potential of selected microorganisms to prevent or treat disease. According to Directive 2001/83/EC, in the European Union (EU), any product intended to prevent or treat disease is defined as a medicinal product and requires a marketing authorization by competent authorities prior to commercialization. Even if the pharmaceutical regulatory framework is harmonized at the EU level, obtaining marketing authorisations for medicinal products remains very challenging for Live Biotherapeutic Products (LBPs). Compared to other medicinal products currently on the market, safety assessment of LBPs represents a real challenge because of their specific characteristics and mode of action. Indeed, LBPs are not intended to reach the systemic circulation targeting distant organs, tissues, or receptors, but rather exert their effect through direct interactions with the complex native microbiota and/or the modulation of complex host-microbiota relation, indirectly leading to distant biological effects within the host. Hence, developers must rely on a thorough risk analysis, and pharmaceutical guidelines for other biological products should be taken into account in order to design relevant non-clinical and clinical development programmes. Here we aim at providing a roadmap for a risk analysis that takes into account the specificities of LBPs. We describe the different risks associated with these products and their interactions with the patient. Then, from that risk assessment, we propose solutions to design non-clinical programmes and First in Human (FIH) early clinical trials appropriate to assess LBP safety.

Diagnostic profiles for precision medicine in systemic sclerosis; stepping forward from single biomarkers towards pathophysiological panels.

Systemic sclerosis (SSc) is an autoimmune disease which is characterized by vasculopathy, tissue fibrosis and activation of the innate and adaptive immune system. Clinical features of the disease consists of skin thickening and internal organ involvement. Due to the heterogeneous nature of the disease it is difficult to predict disease progression and complications. Despite the discovery of novel autoantibodies associated with SSc, there is an unmet need for biomarkers for diagnosis, disease progression and response to treatment. To date, the use of single (surrogate) biomarkers for these purposes has been unsuccessful. Combining multiple biomarkers in to predictive panels or ultimately algorithms could be more precise. Given the limited therapeutic options and poor prognosis of many SSc patients, a better understanding of the immune-pathofysiological profiles might aid to an adjusted therapeutic approach. Therefore, we set out to explore immunological fingerprints in various clinically defined forms of SSc. We used multilayer profiling to identify unique immune profiles underlying distinct autoantibody signatures. These immune profiles could fill the unmet need for prognosis and response to therapy in SSc. Here, we present 3 pathophysiological fingerprints in SSc based on the expression of circulating antibodies, vascular markers and immunomodulatory mediators.

Magnesium prevents vascular calcification in Klotho deficiency.

Klotho knock-out mice are an important model for vascular calcification, which is associated with chronic kidney disease. In chronic kidney disease, serum magnesium inversely correlates with vascular calcification. Here we determine the effects of serum magnesium on aortic calcification in Klotho knock-out mice treated with a minimal or a high magnesium diet from birth. After eight weeks, serum biochemistry and aorta and bone tissues were studied. Protective effects of magnesium were characterized by RNA-sequencing of the aorta and micro-CT analysis was performed to study bone integrity. A high magnesium diet prevented vascular calcification and aortic gene expression of Runx2 and matrix Gla protein found in such mice on the minimal magnesium diet. Differential expression of inflammation and extracellular matrix remodeling genes accompanied the beneficial effects of magnesium on calcification. High dietary magnesium did not affect serum parathyroid hormone, 1,25-dihydroxyvitamin D3 or calcium. High magnesium intake prevented vascular calcification despite increased fibroblast growth factor-23 and phosphate concentration in the knock-out mice. Compared to mice on the minimal magnesium diet, the high magnesium diet reduced femoral bone mineral density by 20% and caused excessive osteoid formation indicating osteomalacia. Osteoclast activity was unaffected by the high magnesium diet. In Saos-2 osteoblasts, magnesium supplementation reduced mineralization independent of osteoblast function. Thus, high dietary magnesium prevents calcification in Klotho knock-out mice. These effects are potentially mediated by reduction of inflammatory and extracellular matrix remodeling pathways within the aorta. Hence magnesium treatment may be promising to prevent vascular calcification, but the risk for osteomalacia should be considered.

Establishing a health-based recommended occupational exposure limit for nitrous oxide using experimental animal data - A systematic review protocol.

Nitrous oxide (N 2 O) is widely used as inhalation analgesic and anaesthetic in medical, paramedical, and veterinary practice. Previous evaluations resulted in classification of N 2 O as a possible risk factor for adverse reproductive health outcomes based on evidence from animal data. Available human data were considered inadequate, partly due to the possibility that other risk factors, such as co-exposures to other inhalation anaesthetics may have contributed to the adverse outcomes. As no substantial new human evidence has emerged since previous evaluations, this protocol describes a planned systematic review of the evidence obtained from animal studies. The aim is to assess the available evidence on the effects of N 2 O on reproductive and developmental outcomes in animals to inform a health-based recommended occupational exposure limit (OEL) for N 2 O. Comprehensive search strategies were designed to retrieve animal studies addressing N 2 O exposure from PubMed, EMBASE, and Web of Science. Screening of the studies retrieved will be performed by at least two independent reviewers, while discrepancies will be resolved by reaching consensus through repeated review and discussions. Articles will be included according to criteria specified in this protocol. Outcome data relevant for reproduction and development will be extracted and risk of bias will be assessed by two independent reviewers using the SYRCLE's risk of bias tool. Primary reproductive and developmental outcomes of interest will be the number of resorptions, malformations, and birth weight. We will focus on dose-response studies that allow to derive an OEL with the benchmark dose (BMD) approach. Adverse outcomes occurring at doses that are equivalent to the exposures occurring in human occupational settings will be particularly relevant for dose-response modelling. The proposed review has not been performed before. We will follow the procedures specified in this protocol. We will adhere to guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), adapted for animal studies. Ethical approval will not be required, as the review will use existing data available in the public domain.

Biosynthetic homeostasis and resilience of the complement system in health and infectious disease.

BACKGROUND: The complement system is a central component of the innate immune system. Constitutive biosynthesis of complement proteins is essential for homeostasis. Dysregulation as a consequence of genetic or environmental cues can lead to inflammatory syndromes or increased susceptibility to infection. However, very little is known about steady state levels in children or its kinetics during infection. METHODS: With a newly developed multiplex mass spectrometry-based method we analyzed the levels of 32 complement proteins in healthy individuals and in a group of pediatric patients infected with bacterial or viral pathogens. FINDINGS: In plasma from young infants we found reduced levels of C4BP, ficolin-3, factor B, classical pathway components C1QA, C1QB, C1QC, C1R, and terminal pathway components C5, C8, C9, as compared to healthy adults; whereas the majority of complement regulating (inhibitory) proteins reach adult levels at very young age. Both viral and bacterial infections in children generally lead to a slight overall increase in complement levels, with some exceptions. The kinetics of complement levels during invasive bacterial infections only showed minor changes, except for a significant increase and decrease of CRP and clusterin, respectively. INTERPRETATION: The combination of lower levels of activating and higher levels of regulating complement proteins, would potentially raise the threshold of activation, which might lead to suppressed complement activation in the first phase of life. There is hardly any measurable complement consumption during bacterial or viral infection. Altogether, expression of the complement proteins appears surprisingly stable, which suggests that the system is continuously replenished. FUND: European Union's Horizon 2020, project PERFORM, grant agreement No. 668303.

Magnesium deficiency prevents high-fat-diet-induced obesity in mice.

AIMS/HYPOTHESIS: Hypomagnesaemia (blood Mg2+ <0.7 mmol/l) is a common phenomenon in individuals with type 2 diabetes. However, it remains unknown how a low blood Mg2+ concentration affects lipid and energy metabolism. Therefore, the importance of Mg2+ in obesity and type 2 diabetes has been largely neglected to date. This study aims to determine the effects of hypomagnesaemia on energy homeostasis and lipid metabolism. METHODS: Mice (n = 12/group) were fed either a low-fat diet (LFD) or a high-fat diet (HFD) (10% or 60% of total energy) in combination with a normal- or low-Mg2+ content (0.21% or 0.03% wt/wt) for 17 weeks. Metabolic cages were used to investigate food intake, energy expenditure and respiration. Blood and tissues were taken to study metabolic parameters and mRNA expression profiles, respectively. RESULTS: We show that low dietary Mg2+ intake ameliorates HFD-induced obesity in mice (47.00 ± 1.53 g vs 38.62 ± 1.51 g in mice given a normal Mg2+-HFD and low Mg2+-HFD, respectively, p < 0.05). Consequently, fasting serum glucose levels decreased and insulin sensitivity improved in low Mg2+-HFD-fed mice. Moreover, HFD-induced liver steatosis was absent in the low Mg2+ group. In hypomagnesaemic HFD-fed mice, mRNA expression of key lipolysis genes was increased in epididymal white adipose tissue (eWAT), corresponding to reduced lipid storage and high blood lipid levels. Low Mg2+-HFD-fed mice had increased brown adipose tissue (BAT) Ucp1 mRNA expression and a higher body temperature. No difference was observed in energy expenditure between the two HFD groups. CONCLUSIONS/INTERPRETATION: Mg2+-deficiency abrogates HFD-induced obesity in mice through enhanced eWAT lipolysis and BAT activity.

Primary cilia-regulated transcriptome in the renal collecting duct.

Renal tubular cells respond to mechanical stimuli generated by urinary flow to regulate the activity and transcript abundance of important genes for ion handling, cellular homeostasis, and proper renal development. The primary cilium, a mechanosensory organelle, is postulated to regulate this mRNA response. The aim of this study is to reveal the transcriptome changes of tubular epithelia in response to fluid flow and determine the role of primary cilia in this process. Inner-medullary collecting duct (CD) cells were subjected to either static or physiologically relevant fluid flow (∼0.6 dyn/cm2). RNA-sequencing analysis of ciliated cells subjected to fluid flow showed up-regulation of 1379 genes and down-regulation of 1294 genes compared with static control cells. Strikingly, only 54 of these genes were identified as gene candidates sensitive to primary cilia sensing of fluid flow, of which 16 were linked to ion or water transport pathways in the CD. Validation by quantitative real-time PCR revealed that only the expression of transferrin receptor, which is involved in iron transport; and tribbles pseudokinase 3, which is involved in insulin signaling, were unequivocally regulated by primary cilia sensing of fluid flow. This study shows that the involvement of primary cilia in ion transport in the collecting duct is exceptionally specific.-Mohammed, S. G., Arjona, F. J., Verschuren, E. H. J., Bakey, Z., Alkema, W., van Hijum, S., Schmidts, M., Bindels, R. J. M., Hoenderop, J. G. J. Primary cilia-regulated transcriptome in the renal collecting duct.

Strain-Dependent Transcriptome Signatures for Robustness in Lactococcus lactis.

Recently, we demonstrated that fermentation conditions have a strong impact on subsequent survival of Lactococcus lactis strain MG1363 during heat and oxidative stress, two important parameters during spray drying. Moreover, employment of a transcriptome-phenotype matching approach revealed groups of genes associated with robustness towards heat and/or oxidative stress. To investigate if other strains have similar or distinct transcriptome signatures for robustness, we applied an identical transcriptome-robustness phenotype matching approach on the L. lactis strains IL1403, KF147 and SK11, which have previously been demonstrated to display highly diverse robustness phenotypes. These strains were subjected to an identical fermentation regime as was performed earlier for strain MG1363 and consisted of twelve conditions, varying in the level of salt and/or oxygen, as well as fermentation temperature and pH. In the exponential phase of growth, cells were harvested for transcriptome analysis and assessment of heat and oxidative stress survival phenotypes. The variation in fermentation conditions resulted in differences in heat and oxidative stress survival of up to five 10-log units. Effects of the fermentation conditions on stress survival of the L. lactis strains were typically strain-dependent, although the fermentation conditions had mainly similar effects on the growth characteristics of the different strains. By association of the transcriptomes and robustness phenotypes highly strain-specific transcriptome signatures for robustness towards heat and oxidative stress were identified, indicating that multiple mechanisms exist to increase robustness and, as a consequence, robustness of each strain requires individual optimization. However, a relatively small overlap in the transcriptome responses of the strains was also identified and this generic transcriptome signature included genes previously associated with stress (ctsR and lplL) and novel genes, including nanE and genes encoding transport proteins. The transcript levels of these genes can function as indicators of robustness and could aid in selection of fermentation parameters, potentially resulting in more optimal robustness during spray drying.

Draft Genome Sequence of Lactobacillus delbrueckii subsp. bulgaricus LBB.B5.

Lactobacillus delbrueckii subsp. bulgaricus LBB.B5 originates from homemade Bulgarian yogurt and was selected for its ability to form a strong association with Streptococcus thermophilus The genome sequence will facilitate elucidating the genetic background behind the contribution of LBB.B5 to the taste and aroma of yogurt and its exceptional protocooperation with S. thermophilus.

High-throughput screening of a large collection of non-conventional yeasts reveals their potential for aroma formation in food fermentation.

Saccharomyces yeast species are currently the most important yeasts involved in industrial-scale food fermentations. However, there are hundreds of other yeast species poorly studied that are highly promising for flavour development, some of which have also been identified in traditional food fermentations. This work explores natural yeast biodiversity in terms of aroma formation, with a particular focus on aromas relevant for industrial fermentations such as wine and beer. Several non-Saccharomyces species produce important aroma compounds such as fusel alcohols derived from the Ehrlich pathway, acetate esters and ethyl esters in significantly higher quantities than the well-known Saccharomyces species. These species are Starmera caribaea, Hanseniaspora guilliermondii, Galactomyces geotrichum, Saccharomycopsis vini and Ambrosiozyma monospora. Certain species revealed a strain-dependent flavour profile while other species were very homogenous in their flavour profiles. Finally, characterization of a selected number of yeast species using valine or leucine as sole nitrogen sources indicates that the mechanisms of regulation of the expression of the Ehrlich pathway exist amongst non-conventional yeast species.