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Biology subjects

Gross, S.

Publications and source records attributed to Gross, S..

33 records · Page 2Linked to original sources

A Novel Imaging Mass Spectrometry Computational Tool for Biomedical Discovery: Untargeted pixel-by-pixel imaging of Metabolite Ratio Pairs

Mass spectrometry imaging (MSI) is a powerful technology used to define the spatial distribution and relative abundance of metabolites across tissue cryosections. While software packages exist for pixel-by-pixel individual metabolite and limited target pairs of ratio imaging, the research community lacks an easy computing and application tool that images any metabolite abundance ratio pairs. Importantly, recognition of correlated metabolite pairs may contribute to the discovery of unanticipated molecules in shared metabolic pathways. Here, we describe the development and implementation of an untargeted R package workflow for pixel-by-pixel ratio imaging of all metabolites detected in an MSI experiment. Considering untargeted MSI studies of murine brain and embryogenesis, we demonstrate that ratio imaging minimizes systematic data variation introduced by sample handling, markedly enhances spatial image contrast, and reveals previously unrecognized metabotype-distinct tissue regions. Furthermore, ratio imaging facilitates identification of novel regional biomarkers and provides anatomical information regarding spatial distribution of metabolite-linked biochemical pathways. The algorithm described herein is applicable to any MSI dataset containing spatial information for metabolites, peptides or proteins, offering a potent hypothesis generation tool to enhance knowledge obtained from current spatial metabolite profiling technologies.

bioinformatics↗

SGLT2 inhibitors attenuate endothelial to mesenchymal transition and cardiac fibroblast activation

Beneficial effects of sodium glucose co-transporter 2 inhibitors (SGLT2is) in cardiovascular diseases have been extensively reported leading to the inclusion of these drugs in the treatment guidelines for heart failure. However, molecular actions especially on non-myocyte cells remain uncertain. We observed dose-dependent inhibitory effects of two SGLT2is, dapagliflozin (DAPA) and empagliflozin (EMPA), on inflammatory signaling in human umbilical vein endothelial cells (HUVECs). Proteomics analyses and subsequent enrichment analyses discovered profound effects of these SGLT2is on proteins involved in mitochondrial respiration and actin cytoskeleton. Validation in functional oxygen consumption measurements as well as tube formation and migration assays revealed strong impacts of DAPA. Considering that most influenced parameters played central roles in endothelial to mesenchymal transition (EndMT), we performed in vitro EndMT assays and identified substantial reduction of mesenchymal and fibrosis marker expression as well as changes in cellular morphology upon treatment with SGLT2is. In line, human cardiac fibroblasts (HCFs) exposed to DAPA showed less proliferation, reduced ATP production, and decelerated migration capacity while less extensive impacts were observed upon EMPA. Mechanistically, sodium proton exchanger 1 (NHE1) as well as sodium-myoinositol cotransporter (SMIT) and sodium-multivitamin cotransporter (SMVT) could be identified as relevant targets of SGLT2is in non-myocyte cardiovascular cells as validated by individual siRNA-knockdown experiments. In summary, we found comprehensive beneficial effects of SGLT2is on human endothelial cells and cardiac fibroblasts. The results of this study therefore support a distinct effect of selected SGLT2i on non-myocyte cardiovascular cells and grant further insights into potential molecular mode of action of these drugs.

pharmacology and toxicology↗

The calcium channel Orai1 is required for osteoblast development: studies in a chimeric mouse with variable in vivo Runx-cre deletion of Orai-1

The calcium-selective ion channel Orai1 has a complex role in bone homeostasis, with defects in both bone production and resorption detected in Orai1 germline knock-out mice. To determine whether Orai1 has a direct, cell-intrinsic role in osteoblast differentiation and function, we bred Orai1 flox/flox (Orai1f/f) mice with Runx2-cre mice to eliminate its expression in osteoprogenitor cells. Interestingly, Orai1 was expressed in a mosaic pattern in Orai1f/f-Runx2-cre bone. Specifically, antibody labeling for Orai1 in vertebral sections was uniform in wild type animals, but patchy regions in Orai1f/f-Runx2-cre bone revealed Orai1 loss while in other areas expression persisted. Nevertheless, by micro-CT, bones from Orai1f/f-Runx2-cre mice showed reduced bone mass overall, with impaired bone formation identified by dynamic histomorphometry. Cortical surfaces of Orai1f/f-Runx2-cre vertebrae however exhibited patchy defects. In cell culture, Orai1-negative osteoblasts showed profound reductions in store-operated Ca2+ entry, exhibited decreased alkaline phosphatase activity, and had markedly impaired substrate mineralization. We conclude that defective bone formation observed in the absence of Orai1 reflects an intrinsic role for Orai1 in differentiating osteoblasts.

developmental biology↗

Automated bioprocess feedback operation in a high throughput facility via the integration of a mobile robotic lab assistant

Biotechnological processes development is challenging due to the sheer variety of process parameters. For efficient upstream development parallel cultivation systems have proven to reduce costs and associated timelines successfully, while offering excellent process control. However, the degree of automation of such small scale systems is comparably low and necessary sample analysis requires manual steps. Although the subsequent analysis can be performed in a high-throughput manner, the integration of analytic devices remains challenging. Especially, when cultivation and analysis laboratories are spatially separated. Mobile robots offer a potential solution, but the implementation in research laboratories is not widely adopted. Our approach demonstrates the integration of a small scale cultivation system into a liquid handling station for an automated sample procedure. The samples are transferred via a mobile robotic lab assistant and subsequently analysed by a high-throughput analyzer. The process data is stored in a centralized database. The mobile robotic workflow guarantees a flexible solution for device integration and facilitates automation. Restrictions regarding spatial separation of devices are circumvented, enabling a modular platform throughout different laboratories. The presented cultivation platform is evaluated based on industrial relevant E. coli BW25113 high cell density fed-batch cultivation. Here its suitability for accelerating bioprocess development is proven. The necessary magnesium addition for reaching high cell densities in mineral salt medium is automated via a feedback operation loop. The feedback operation loop demonstrates the possibility for advanced control options. This study sets the foundation for a fully integrated facility with different cultivation scales sharing the same data infrastructure, where the mobile robotic lab assistant physically connects the devices.

bioengineering↗

Optimal operation of parallel mini-bioreactors in bioprocess development using multi-stage MPC

Bioprocess development is commonly characterized by long development times, especially in the early screening phase. After promising candidates have been pre-selected in screening campaigns, an optimal operating strategy has to be found and verified under conditions similar to production. Cultivating cells with pulse-based feeding and thus exposing them to oscillating feast and famine phases has shown to be a powerful approach to study microorganisms closer to industrial bioreactor conditions. In view of the large number of strains and the process conditions to be tested, high-throughput cultivation systems provide an essential tool to sample the large design space in short time. We have recently presented a comprehensive platform, consisting of two liquid handling stations coupled with a model-based experimental design and operation framework to increase the efficiency in High Throughput bioprocess development. Using calibrated macro-kinetic growth models, the platform has been successfully used for the development of scale-down fed-batch cultivations in parallel mini-bioreactor systems. However, it has also been shown that parametric uncertainties in the models can significantly affect the prediction accuracy and thus the reliability of optimized cultivation strategies. To tackle this issue, we implemented a multi-stage Model Predictive Control (MPC) strategy to fulfill the experimental objectives under tight constraints despite the uncertainty in the parameters and the measurements. Dealing with uncertainties in the parameters is of major importance, since constraint violation would easily occur otherwise, which in turn could have adverse effects on the quality of the heterologous protein produced. Multi-stage approaches build up scenario tree, based on the uncertainty that can be encountered and computing optimal inputs that satisfy the constrains despite of such uncertainties. Using the feedback information gained through the evolution along the tree, the control approach is significantly more robust than standard MPC approaches without being overly conservative. We show in this study that the application of multi-stage MPC can increase the number of successful experiments, by applying this methodology to a mini-bioreactor cultivation operated in parallel.

bioengineering↗

Vocal tract allometry in a mammalian vocal learner

Acoustic allometry occurs when features of animal vocalisations can be predicted from body size measurements. Despite this being considered the norm, allometry sometimes breaks, resulting in species sounding smaller or larger than expected for their size. A recent hypothesis suggests that allometry-breaking mammals cluster into two groups: those with anatomical adaptations to their vocal tracts and those capable of learning new sounds (vocal learners). Here we test which mechanism is used to escape from acoustic allometry by probing vocal tract allometry in a proven mammalian vocal learner, the harbour seal (Phoca vitulina). We test whether vocal tract structures and body size scale allometrically in 68 young individuals. We find that both body length and body mass accurately predict vocal tract length and one tracheal dimension. Independently, body length predicts vocal fold length while body mass predicts a second tracheal dimension. All vocal tract measures are larger in weaners than in pups and some structures are sexually dimorphic within age classes. We conclude that harbour seals do comply with anatomical allometric constraints. However, allometry between body size and vocal fold length seems to emerge after puppyhood, suggesting that ontogeny may modulate the anatomy-learning distinction previously hypothesised as clear-cut. We suggest that seals, like other species producing signals that deviate from those expected from their vocal tract dimensions, may break allometry without morphological adaptations. In seals, and potentially other vocal learning mammals, advanced neural control over vocal organs may be the main mechanism for breaking acoustic allometry.

animal behavior and cognition↗

Multiple links between 5-methylcytosine content of mRNA and translation

5-methylcytosine (m5C) is a prevalent base modification in tRNA and rRNA but it also occurs more broadly in the transcriptome, including in mRNA, where it serves incompletely understood molecular functions. In pursuit of potential links of m5C with mRNA translation, we performed polysome profiling of human HeLa cell lysates and subjected RNA from resultant fractions to efficient bisulfite conversion followed by RNA sequencing (bsRNA-seq). Bioinformatic filters for rigorous site calling were devised to reduce technical noise. We obtained [~]1,000 candidate m5C sites in the wider transcriptome, most of which were found in mRNA. Multiple novel sites were validated by amplicon-specific bsRNA-seq in independent samples of either human HeLa, LNCaP and PrEC cells. Furthermore, RNAi-mediated depletion of either the NSUN2 or TRDMT1 m5C:RNA methyltransferases showed a clear dependence on NSUN2 for the majority of tested sites in both mRNAs and noncoding RNAs. Candidate m5C sites in mRNAs are enriched in 5UTRs and near start codons, and are commonly embedded in a local context reminiscent of the NSUN2-dependent m5C sites found in the variable loop of tRNA. Analysing mRNA sites across the polysome profile revealed that modification levels, at bulk and for many individual sites, were inversely correlated with ribosome association. Altogether, these findings emphasise the major role of NSUN2 in making this mark transcriptome-wide and further substantiate a functional interdependence of cytosine methylation level with mRNA translation.

molecular biology↗

The RNA Atlas, a single nucleotide resolution map of the human transcriptome

The human transcriptome consists of various RNA biotypes including multiple types of non-coding RNAs (ncRNAs). Current ncRNA compendia remain incomplete partially because they are almost exclusively derived from the interrogation of small- and polyadenylated RNAs. Here, we present a more comprehensive atlas of the human transcriptome that is derived from matching polyA-, total-, and small-RNA profiles of a heterogeneous collection of nearly 300 human tissues and cell lines. We report on thousands of novel RNA species across all major RNA biotypes, including a hitherto poorly-cataloged class of non-polyadenylated single-exon long non-coding RNAs. In addition, we exploit intron abundance estimates from total RNA-sequencing to test and verify functional regulation by novel non-coding RNAs. Our study represents a substantial expansion of the current catalogue of human ncRNAs and their regulatory interactions. All data, analyses, and results are available in the R2 web portal and serve as a basis to further explore RNA biology and function.

genetics↗

Molecular motor organization and mobility on cargos can overcome a tradeoff between fast binding and run length

Cellular cargos, including lipid droplets and mitochondria, are transported along microtubules using molecular motors such as kinesins. Many experimental and computational studies of cargos with rigidly attached motors, in contrast to many biological cargos that have lipid surfaces that may allow surface mobility of motors. We extend a mechanochemical 3D computational model by adding coupled-viscosity effects to compare different motor arrangements and mobilities. We show that organizational changes can optimize for different objectives: Cargos with clustered motors are transported efficiently, but are slow to bind to microtubules, whereas those with motors dispersed rigidly on their surface bind microtubules quickly, but are transported inefficiently. Finally, cargos with freely-diffusing motors have both fast binding and efficient transport, although less efficient than clustered motors. These results suggest that experimentally observed changes in motor organization may be a control point for transport.

cell biology↗

Antibody cross-reactivity accounts for widespread appearance of m1A in 5 UTRs

N1-methyladenosine (m1A) was recently identified as a new mRNA modification based on its mapping to the 5 UTRs of thousands of mRNAs with an m1A-binding antibody. More recent studies have confirmed the prevalence of m1A, while others have questioned it. To address this discrepancy, we mapped m1A using ultra-deep RNA-Seq datasets based on m1A-induced misincorporations during reverse transcription. Using this approach, we find m1A only in the mitochondrial MT-ND5 transcript. In contrast, when we mapped m1A antibody-binding sites at single-nucleotide resolution, we found binding to transcription start nucleotides in mRNA 5 UTRs. Using different biochemical assays, we find that m1A is not present at these sites. Instead, we find that the m1A antibody exhibits m1A-independent binding to mRNA cap structures. We also tested a new and independently derived m1A antibody. We show that this m1A antibody lacks m7G cap-binding cross-reactivity, and notably does not map to 5 UTRs in the transcriptome. Our data demonstrate that high-stoichiometry m1A sites are rare in the transcriptome and that previous mapping of m1A to mRNA 5 UTRs are due to unintended binding of the m1A antibody to m7G cap structure in mRNA.

molecular biology↗

Hip circumduction is not a compensation for reduced knee flexion angle during gait

It has long been held that hip abduction compensates for reduced swing-phase knee flexion angle, especially in those after stroke. However, there are other compensatory motions such as pelvic obliquity (hip hiking) that could also be used to facilitate foot clearance with greater energy efficiency. Our previous work suggested that hip abduction may not be a compensation for reduced knee flexion after stroke. Previous study applied robotic knee flexion assistance in people with post-stroke Stiff-Knee Gait (SKG) during pre-swing, finding increased abduction despite improved knee flexion and toe clearance. Thus, our hypothesis was that hip abduction is not a compensation for reduced knee flexion. We simulated the kinematics of post-stroke SKG on unimpaired individuals with three factors: a knee orthosis to reduce knee flexion, an ankle-foot orthosis commonly worn by those post-stroke, and matching gait speeds. We compared spatiotemporal measures and kinematics between experimental factors within healthy controls and with a previously recorded cohort of people with post-stroke SKG. We focused on frontal plane motions of hip and pelvis as possible compensatory mechanisms. We observed that regardless of gait speed, knee flexion restriction significantly increased pelvic obliquity (2.79{degrees}, p<0.01) compared to unrestricted walking (1.5{degrees}, p<0.01), but similar to post-stroke SKG (3.4{degrees}). However, those with post-stroke SKG had significantly greater hip abduction (8.2{degrees}) compared to unimpaired individuals with restricted knee flexion (4.2{degrees}, p<0.05). These results show that pelvic obliquity, not hip abduction, compensates for reduced knee flexion angle. Thus, other factors, possibly neural, facilitate exaggerated hip abduction observed in post-stroke SKG.

bioengineering↗

Evaluation of the causal effect of fibrinogen on incident coronary heart disease via Mendelian randomization

BackgroundFibrinogen is an essential hemostatic factor and cardiovascular disease risk factor. Early attempts at evaluating the causal effect of fibrinogen on coronary heart disease (CHD) and myocardial infraction (MI) using Mendelian randomization (MR) used single variant approaches, and did not take advantage of recent genome-wide association studies (GWAS) or multi-variant, pleiotropy robust MR methodologies.\n\nMethods and FindingsWe evaluated evidence for a causal effect of fibrinogen on both CHD and MI using MR. We used both an allele score approach and pleiotropy robust MR models. The allele score was composed of 38 fibrinogen-associated variants from recent GWAS. Initial analyses using the allele score incorporated data from 11 European-ancestry prospective cohorts to examine incidence CHD and MI. We also applied 2 sample MR methods with data from a prevalent CHD and MI GWAS. Results are given in terms of the hazard ratio (HR) or odds ratio (OR), depending on the study design, and associated 95% confidence interval (CI).\n\nIn single variant analyses no causal effect of fibrinogen on CHD or MI was observed. In multi-variant analyses using incidence CHD cases and the allele score approach, the estimated causal effect (HR) of a 1 g/L higher fibrinogen concentration was 1.62 (CI = 1.12, 2.36) when using incident cases and the allele score approach. In 2 sample MR analyses that accounted for pleiotropy, the causal estimate (OR) was reduced to 1.18 (CI = 0.98, 1.42) and 1.09 (CI = 0.89, 1.33) in the 2 most precise (smallest CI) models, out of 4 models evaluated. In the 2 sample MR analyses for MI, there was only very weak evidence of a causal effect in only 1 out of 4 models.\n\nConclusionsA small causal effect of fibrinogen on CHD is observed using multi-variant MR approaches which account for pleiotropy, but not single variant MR approaches. Taken together, results indicate that even with large sample sizes and multi-variant approaches MR analyses still cannot exclude the null when estimating the causal effect of fibrinogen on CHD, but that any potential causal effect is likely to be much smaller than observed in epidemiological studies.\n\nAuthor SummaryInitial Mendelian Randomization (MR) analyses of the causal effect of fibrinogen on coronary heart disease (CHD) utilized single variants and did not take advantage of modern, multivariant approaches. This manuscript provides an important update to these initial analyses by incorporating larger sample sizes and employing multiple, modern multi-variant MR approaches to account for pleiotropy. We used incident cases to perform a MR study of the causal effect of fibrinogen on incident CHD and the nested outcome of myocardial infarction (MI) using an allele score approach. Then using data from a case-control genome-wide association study for CHD and MI we performed two sample MR analyses with multiple, pleiotropy robust approaches. Overall, the results indicated that associations between fibrinogen and CHD in observational studies are likely upwardly biased from any underlying causal effect. Single variant MR approaches show little evidence of a causal effect of fibrinogen on CHD or MI. Multi-variant MR analyses of fibrinogen on CHD indicate there may be a small positive effect, however this result needs to be interpreted carefully as the 95% confidence intervals were still consistent with a null effect. Multi-variant MR approaches did not suggest evidence of even a small causal effect of fibrinogen on MI.

genetics↗

Identification of a Distinct Metabolomic Subtype of Sporadic ALS Patients

Sporadic amyotrophic lateral sclerosis (sALS) is a progressive motor neuron disease resulting in paralysis and death. Genes responsible for familial ALS have been identified, however the molecular basis for sALS is unknown. To discover metabotypic biomarkers that inform on disease etiology, untargeted metabolite profiling was performed on 77 patient-derived dermal fibroblast lines and 45 age/sex-matched controls. Surprisingly, 25% of sALS lines showed upregulated methionine-derived homocysteine, channeled to cysteine and glutathione (GSH). Stable isotope tracing of [U-13C]-glucose showed activation of the trans-sulfuration pathway, associated with accelerated glucose flux into the TCA cycle, glutamate, GSH, alanine, aspartate, acylcarnitines and nucleotide phosphates. A four-molecule support vector machine model distinguished the sALS subtype from controls with 97.5% accuracy. Plasma metabolite profiling identified increased taurine as a hallmark metabolite for this sALS subset, suggesting systemic perturbation of cysteine metabolism. Furthermore, integrated multiomics (mRNAs/microRNAs/metabolites) identified the super-trans-sulfuration pathway as a top hit for the sALS subtype. We conclude that sALS can be stratified into distinct metabotypes, providing for future development of personalized therapies that offer new hope to sufferers.

neuroscience↗

Replacing reprogramming factors with antibodies selected from autocrine antibody libraries

Signaling pathways initiated at the membrane establish and maintain cell fate during development and can be harnessed in the nucleus to generate induced pluripotent stem cells (iPSCs) from differentiated cells. Yet, the impact of extracellular signaling on reprogramming to pluripotency has not been systematically addressed. Here, we screen a lentiviral library encoding {small tilde}100 million secreted and membrane-bound antibodies and identify multiple antibodies that can replace Sox2/c-Myc or Oct4 during reprogramming. We show that one Sox2-replacing antibody initiates reprogramming by antagonizing the membrane-associated protein Basp1, thereby inducing nuclear factors WT1 and Esrrb/Lin28 independent of Sox2. By successively manipulating this pathway we identify three new methods to generate iPSCs. This study expands current knowledge of reprogramming methods and mechanisms and establishes unbiased selection from autocrine antibody libraries as a powerful orthogonal platform to discover new biologics and pathways regulating pluripotency and cell fate.

cell biology↗

Creating a universal SNP and small indel variant caller with deep neural networks

Next-generation sequencing (NGS) is a rapidly evolving set of technologies that can be used to determine the sequence of an individuals genome1 by calling genetic variants present in an individual using billions of short, errorful sequence reads2. Despite more than a decade of effort and thousands of dedicated researchers, the hand-crafted and parameterized statistical models used for variant calling still produce thousands of errors and missed variants in each genome3,4. Here we show that a deep convolutional neural network5 can call genetic variation in aligned next-generation sequencing read data by learning statistical relationships (likelihoods) between images of read pileups around putative variant sites and ground-truth genotype calls. This approach, called DeepVariant, outperforms existing tools, even winning the \"highest performance\" award for SNPs in a FDA-administered variant calling challenge. The learned model generalizes across genome builds and even to other mammalian species, allowing non-human sequencing projects to benefit from the wealth of human ground truth data. We further show that, unlike existing tools which perform well on only a specific technology, DeepVariant can learn to call variants in a variety of sequencing technologies and experimental designs, from deep whole genomes from 10X Genomics to Ion Ampliseq exomes. DeepVariant represents a significant step from expert-driven statistical modeling towards more automatic deep learning approaches for developing software to interpret biological instrumentation data.

genomics↗