Leuk Lymphoma. 2021 Mar 8:1-5. doi: 10.1080/10428194.2021.1894644. Online ahead of print.

NO ABSTRACT

PMID:33685326 | DOI:10.1080/10428194.2021.1894644

Int J Med Microbiol. 2021 Feb 25;311(3):151486. doi: 10.1016/j.ijmm.2021.151486. Online ahead of print.

ABSTRACT

The intestinal epithelium is a monolayer of polarized columnar cells that act as a border between the host and its environment and are the first line of defence against the luminal microbes. In addition to providing a physical barrier, the epithelium possesses a multitude of active mechanisms to fight invading pathogens and regulate the composition and spatial distribution of commensals. The different epithelial cell types have unique functions in this context, and crosstalk with the immune system further modulates their intricate antimicrobial responses. The epithelium is organized into clonal crypt units with a high cellular turnover that is driven by stem cells located at the base. There is increasing evidence that this anatomical organization, the stem cell turnover, and the lineage determination processes are essential for barrier maintenance. These processes can be modulated by microbes directly or by the immune responses to enteric pathogens, resulting in a rapid and efficient adaptation of the epithelium to environmental perturbations, injuries, and infections. Here we discuss the complex host-microbial interactions that shape the mucosa and how the epithelium maintains and re-establishes homeostasis after infection.

PMID:33684844 | DOI:10.1016/j.ijmm.2021.151486

Genomics Proteomics Bioinformatics. 2021 Mar 5:S1672-0229(21)00058-9. doi: 10.1016/j.gpb.2020.05.005. Online ahead of print.

ABSTRACT

The rapid advancement of single-cell technologies has shed new light on the complex mechanisms of cellular heterogeneity. However, compared to bulk RNA sequencing (RNA-seq), single-cell RNA-seq (scRNA-seq) suffers from higher noise and lower coverage, which brings new computational difficulties. Based on statistical independence, cell-specific network (CSN) is able to quantify the overall associations between genes for each cell, yet suffering from a problem of overestimation related to indirect effects. To overcome this problem, we propose the c-CSN method, which can construct the conditional cell-specific network (CCSN) for each cell. c-CSN method can measure the direct associations between genes by eliminating the indirect associations. c-CSN can be used for cell clustering and dimension reduction on a network basis of single cells. Intuitively, each CCSN can be viewed as the transformation from less "reliable" gene expression to more "reliable" gene-gene associations in a cell. Based on CCSN, we further design network flow entropy (NFE) to estimate the differentiation potency of a single cell. A number of scRNA-seq datasets were used to demonstrate the advantages of our approach. (1) One direct association network is generated for one cell. (2) Most existing scRNA-seq methods designed for gene expression matrices are also applicable to c-CSN-transformed degree matrices. (3) CCSN-based NFE helps resolving the direction of differentiation trajectories by quantifying the potency of each cell. c-CSN is publicly available at https://github.com/LinLi-0909/c-CSN.

PMID:33684532 | DOI:10.1016/j.gpb.2020.05.005

Environ Microbiol. 2021 Mar 8. doi: 10.1111/1462-2920.15453. Online ahead of print.

ABSTRACT

The structure and diversity of all open microbial communities are shaped by individual births, deaths, speciation and immigration events; the precise timings of these events are unknowable and unpredictable. This randomness is manifest as ecological drift in the population dynamics, the importance of which has been a source of debate for decades. There are theoretical reasons to suppose that drift would be imperceptible in large microbial communities, but this is at odds with circumstantial evidence that effects can be seen even in huge, complex communities. To resolve this dichotomy we need to observe dynamics in simple systems where key parameters, like migration, birth and death rates can be directly measured. We monitored the dynamics in the abundance of two genetically modified strains of Escherichia coli, with tuneable growth characteristics, that were mixed and continually fed into 10 identical chemostats. We demonstrated that the effects of demographic (non-environmental) stochasticity are very apparent in the dynamics. However, they do not conform to the most parsimonious and commonly applied mathematical models, where each stochastic event is independent. For these simple models to reproduce the observed dynamics we need to invoke an "effective community size", which is smaller than the census community size. This article is protected by copyright. All rights reserved.

PMID:33684262 | DOI:10.1111/1462-2920.15453

Environ Microbiol. 2021 Mar 8. doi: 10.1111/1462-2920.15450. Online ahead of print.

ABSTRACT

The bacterium Paenibacillus polymyxa is found naturally in diverse niches. Microbiome analyses have revealed enrichment in the genus Paenibacillus in soils under different adverse conditions, which is often accompanied by improved growth conditions for residing plants. Furthermore, Paenibacillus is a member of the core microbiome of several agriculturally important crops, making its close association with plants an interesting research topic. This review covers the versatile interaction potential of P. polymyxa with plants and its applicability in industry and agriculture. Thanks to its array of produced compounds and traits, P. polymyxa is potentially an efficient plant growth-promoting bacterium, with the potential of biofertilization, biocontrol and protection against abiotic stresses. By contrast, cases of phytotoxicity of P. polymyxa have been described as well, in which growth conditions seem to play a key role. Because of its versatile character, we propose this bacterial species as an outstanding model for future studies on host-microbe communications and on the manner how the environment can influence these interactions. This article is protected by copyright. All rights reserved.

PMID:33684235 | DOI:10.1111/1462-2920.15450

PLoS One. 2021 Mar 8;16(3):e0243517. doi: 10.1371/journal.pone.0243517. eCollection 2021.

ABSTRACT

Deuterium (D), the second most abundant isotope of hydrogen is present in natural waters at an approximate concentration of 145-155 ppm (ca. 1.5E-4 atom/atom). D is known to influence various biological processes due to its physical and chemical properties, which significantly differ from those of hydrogen. For example, increasing D-concentration to >1000-fold above its natural abundance has been shown to increase the frequency of genetic mutations in several species. An interesting deterministic hypothesis, formulated with the intent of explaining the mechanism of D-mutagenicity is based on the calculation that the theoretical probability of base pairs to comprise two adjacent D-bridges instead of H-bridges is 2.3E-8, which is equal to the mutation rate of certain species. To experimentally challenge this hypothesis, and to infer the mutagenicity of D present at natural concentrations, we investigated the effect of a nearly 100-fold reduction of D concentration on the bacterial mutation rate. Using fluctuation tests, we measured the mutation rate of three Escherichia coli genes (cycA, ackA and galK) in media containing D at either <2 ppm or 150 ppm concentrations. Out of 15 pair-wise fluctuation analyses, nine indicated a significant decrease, while three marked the significant increase of the mutation/culture value upon D-depletion. Overall, growth in D-depleted minimal medium led to a geometric mean of 0.663-fold (95% confidence interval: 0.483-0.911) change in the mutation rate. This falls nowhere near the expected 10,000-fold reduction, indicating that in our bacterial systems, the effect of D abundance on the formation of point mutations is not deterministic. In addition, the combined results did not display a statistically significant change in the mutation/culture value, the mutation rate or the mutant frequency upon D-depletion. The potential mutagenic effect of D present at natural concentrations on E. coli is therefore below the limit of detection using the indicated methods.

PMID:33684107 | DOI:10.1371/journal.pone.0243517

PLoS Comput Biol. 2021 Mar 8;17(3):e1008256. doi: 10.1371/journal.pcbi.1008256. Online ahead of print.

ABSTRACT

Modern spatial transcriptomics methods can target thousands of different types of RNA transcripts in a single slice of tissue. Many biological applications demand a high spatial density of transcripts relative to the imaging resolution, leading to partial mixing of transcript rolonies in many voxels; unfortunately, current analysis methods do not perform robustly in this highly-mixed setting. Here we develop a new analysis approach, BARcode DEmixing through Non-negative Spatial Regression (BarDensr): we start with a generative model of the physical process that leads to the observed image data and then apply sparse convex optimization methods to estimate the underlying (demixed) rolony densities. We apply BarDensr to simulated and real data and find that it achieves state of the art signal recovery, particularly in densely-labeled regions or data with low spatial resolution. Finally, BarDensr is fast and parallelizable. We provide open-source code as well as an implementation for the 'NeuroCAAS' cloud platform.

PMID:33684106 | DOI:10.1371/journal.pcbi.1008256

PLoS Comput Biol. 2021 Mar 8;17(3):e1008571. doi: 10.1371/journal.pcbi.1008571. Online ahead of print.

ABSTRACT

During early mammalian embryo development, a small number of cells make robust fate decisions at particular spatial locations in a tight time window to form inner cell mass (ICM), and later epiblast (Epi) and primitive endoderm (PE). While recent single-cell transcriptomics data allows scrutinization of heterogeneity of individual cells, consistent spatial and temporal mechanisms the early embryo utilize to robustly form the Epi/PE layers from ICM remain elusive. Here we build a multiscale three-dimensional model for mammalian embryo to recapitulate the observed patterning process from zygote to late blastocyst. By integrating the spatiotemporal information reconstructed from multiple single-cell transcriptomic datasets, the data-informed modeling analysis suggests two major processes critical to the formation of Epi/PE layers: a selective cell-cell adhesion mechanism (via EphA4/EphrinB2) for fate-location coordination and a temporal attenuation mechanism of cell signaling (via Fgf). Spatial imaging data and distinct subsets of single-cell gene expression data are then used to validate the predictions. Together, our study provides a multiscale framework that incorporates single-cell gene expression datasets to analyze gene regulations, cell-cell communications, and physical interactions among cells in complex geometries at single-cell resolution, with direct application to late-stage development of embryogenesis.

PMID:33684098 | DOI:10.1371/journal.pcbi.1008571

Elife. 2021 Mar 8;10:e64478. doi: 10.7554/eLife.64478.

ABSTRACT

Methods for measuring gut microbiota biochemical activities in vivo are needed to characterize its functional states in health and disease. To illustrate one approach, an arabinan-containing polysaccharide was isolated from pea fiber, its structure defined, and forward genetic and proteomic analyses used to compare its effects, versus unfractionated pea fiber and sugar beet arabinan, on a human gut bacterial strain consortium in gnotobiotic mice. We produced 'Microbiota Functional Activity Biosensors' (MFABs) consisting of glycans covalently linked to the surface of fluorescent paramagnetic microscopic glass beads. Three MFABs, each containing a unique glycan/fluorophore combination, were simultaneously orally gavaged into gnotobiotic mice, recovered from their intestines, and analyzed to directly quantify bacterial metabolism of structurally distinct arabinans in different human diet contexts. Colocalizing pea-fiber arabinan and another polysaccharide (glucomannan) on the bead surface enhanced in vivo degradation of glucomannan. MFABs represent a potentially versatile platform for developing new prebiotics and more nutritious foods.

PMID:33684031 | DOI:10.7554/eLife.64478

J Chem Inf Model. 2021 Mar 8. doi: 10.1021/acs.jcim.0c01282. Online ahead of print.

ABSTRACT

One of the grand challenges of this century is modeling and simulating a whole cell. Extreme regulation of an extensive quantity of model and simulation data during whole-cell modeling and simulation renders it a computationally expensive research problem in systems biology. In this article, we present a high-performance whole-cell simulation exploiting modular cell biology principles. We prepare the simulation by dividing the unicellular bacterium, Escherichia coli (E. coli), into subcells utilizing the spatially localized densely connected protein clusters/modules. We set up a Brownian dynamics-based parallel whole-cell simulation framework by utilizing the Hamiltonian mechanics-based equations of motion. Though the velocity Verlet integration algorithm possesses the capability of solving the equations of motion, it lacks the ability to capture and deal with particle-collision scenarios. Hence, we propose an algorithm for detecting and resolving both elastic and inelastic collisions and subsequently modify the velocity Verlet integrator by incorporating our algorithm into it. Also, we address the boundary conditions to arrest the molecules' motion outside the subcell. For efficiency, we define one hashing-based data structure called the cellular dictionary to store all of the subcell-related information. A benchmark analysis of our CUDA C/C++ simulation code when tested on E. coli using the CPU-GPU cluster indicates that the computational time requirement decreases with the increase in the number of computing cores and becomes stable at around 128 cores. Additional testing on higher organisms such as rats and humans informs us that our proposed work can be extended to any organism and is scalable for high-end CPU-GPU clusters.

PMID:33683902 | DOI:10.1021/acs.jcim.0c01282

J Cell Commun Signal. 2021 Mar 8. doi: 10.1007/s12079-021-00609-3. Online ahead of print.

ABSTRACT

Loss of cell differentiation is a hallmark for the progression of oral squamous cell carcinoma (OSCC). Archival Formalin-Fixed Paraffin-Embedded (FFPE) tissues constitute a valuable resource for studying the differentiation of OSCC and can offer valuable insights into the process of tumor progression. In the current study, we performed LC-MS/MS-based quantitative proteomics of FFPE specimens from pathologically-confirmed well-differentiated, moderately-differentiated, and poorly-differentiated OSCC cases. The data were analyzed in four technical replicates, resulting in the identification of 2376 proteins. Of these, 141 and 109 were differentially expressed in moderately-differentiated and poorly differentiated OSCC cases, respectively, compared to well-differentiated OSCC. The data revealed significant metabolic reprogramming with respect to lipid metabolism and glycolysis with proteins belonging to both these processes downregulated in moderately-differentiated OSCC when compared to well-differentiated OSCC. Signaling pathway analysis indicated the alteration of extracellular matrix organization, muscle contraction, and glucose metabolism pathways across tumor grades. The extracellular matrix organization pathway was upregulated in moderately-differentiated OSCC and downregulated in poorly differentiated OSCC, compared to well-differentiated OSCC. PADI4, an epigenetic enzyme transcriptional regulator, and its transcriptional target HIST1H1B were both found to be upregulated in moderately differentiated and poorly differentiated OSCC, indicating epigenetic events underlying tumor differentiation. In conclusion, the findings support the advantage of using high-resolution mass spectrometry-based FFPE archival blocks for clinical and translational research. The candidate signaling pathways identified in the study could be used to develop potential therapeutic targets for OSCC.

PMID:33683571 | DOI:10.1007/s12079-021-00609-3

Elife. 2021 Mar 8;10:e65993. doi: 10.7554/eLife.65993. Online ahead of print.

ABSTRACT

Gene expression levels are influenced by multiple coexisting molecular mechanisms. Some of these interactions, such as those of transcription factors and promoters have been studied extensively. However, predicting phenotypes of gene regulatory networks remains a major challenge. Here, we use a well-defined synthetic gene regulatory network to study in Escherichia coli how network phenotypes depend on local genetic context, i.e. the genetic neighborhood of a transcription factor and its relative position. We show that one gene regulatory network with fixed topology can display not only quantitatively but also qualitatively different phenotypes, depending solely on the local genetic context of its components. Transcriptional read-through is the main molecular mechanism that places one transcriptional unit within two separate regulons without the need for complex regulatory sequences. We propose that relative order of individual transcriptional units, with its potential for combinatorial complexity, plays an important role in shaping phenotypes of gene regulatory networks.

PMID:33683203 | DOI:10.7554/eLife.65993

Elife. 2021 Mar 8;10:e62073. doi: 10.7554/eLife.62073.

ABSTRACT

Although brain temperature has neurobiological and clinical importance, it remains unclear which factors contribute to its daily dynamics and to what extent. Using a statistical approach, we previously demonstrated that hourly brain temperature values co-varied strongly with time spent awake (Hoekstra et al., 2019). Here we develop and make available a mathematical tool to simulate and predict cortical temperature in mice based on a 4-s sleep-wake sequence. Our model estimated cortical temperature with remarkable precision and accounted for 91% of the variance based on three factors: sleep-wake sequence, time-of-day ('circadian'), and a novel 'prior wake prevalence' factor, contributing with 74%, 9%, and 43%, respectively (including shared variance). We applied these optimized parameters to an independent cohort of mice and predicted cortical temperature with similar accuracy. This model confirms the profound influence of sleep-wake state on brain temperature, and can be harnessed to differentiate between thermoregulatory and sleep-wake-driven effects in experiments affecting both.

PMID:33683202 | DOI:10.7554/eLife.62073

Nanomedicine (Lond). 2021 Mar 8. doi: 10.2217/nnm-2020-0358. Online ahead of print.

ABSTRACT

Background: Exploration of the efficiency of metal nanoparticles as adjuvants have reported varying results. Objective: The efficacy of metal nanoparticles as adjuvants was investigated Data sources: Database were searched using the terms 'metal nanoparticles' and 'vaccines'. Study eligibility criteria: Studies in animal models utilizing any metal-based vaccines, where the survival rate was described. Study appraisal: The quality of the studies was examined using aspects of the ARRIVE guidelines and assessment of the risk of bias of included studies. Results: Metal nanoparticle-based adjuvants were more effective compared with control (unvaccinated groups) but have not been more successful in competing with common adjuvants or even antigens alone. Limitation: More than 75% of articles have used only gold nanoparticles. Conclusion: Nano-adjuvants do not have a significant effect on reducing mortality.

PMID:33683147 | DOI:10.2217/nnm-2020-0358

Mol Nutr Food Res. 2021 Mar 8:e2000848. doi: 10.1002/mnfr.202000848. Online ahead of print.

ABSTRACT

SCOPE: Infant formula (IF) uses besides vegetable fats also bovine milk fat, which differs in triacylglycerol (TAG) structure. Furthermore, it differs in fatty acid (FA) composition. Whether changing fat source in IF affects postprandial energy metabolism, lipemic response and blood lipid profile is unknown.

METHODS AND RESULTS: A proof-of-principle study, with a randomized controlled double-blind cross-over design, was conducted. Twenty healthy male adults consumed drinks with either 100% vegetable fat (VEG) or 67% bovine milk fat and 33% vegetable fat (BOV), on two separate days. For a detailed insight in the postprandial responses, indirect calorimetry was performed continuously, and venous blood samples were taken every 30 minutes, until 5 hours postprandially. No differences in postprandial energy metabolism, serum lipids, lipoprotein, or chylomicron concentrations were observed between drinks. After consumption of VEG-drink C18:2n-6 in serum increased. Observed differences in chylomicron FA profile reflected differences in initial FA profile of test drinks. Serum ketone bodies concentrations increased following consumption of BOV-drink.

CONCLUSIONS: The use of bovine milk fat in IF does neither affect postprandial energy metabolism nor lipemic response in healthy adults, but alters postprandial FA profiles and ketone metabolism. Whether the exact same effects occur in infants requires experimental verification. This article is protected by copyright. All rights reserved.

PMID:33682997 | DOI:10.1002/mnfr.202000848

J Vis Exp. 2021 Feb 18;(168). doi: 10.3791/62307.

ABSTRACT

Three-dimensional (3D) in vitro models of skeletal muscle are a valuable advancement in biomedical research as they afford the opportunity to study skeletal muscle reformation and function in a scalable format that is amenable to experimental manipulations. 3D muscle culture systems are desirable as they enable scientists to study skeletal muscle ex vivo in the context of human cells. 3D in vitro models closely mimic aspects of the native tissue structure of adult skeletal muscle. However, their universal application is limited by the availability of platforms that are simple to fabricate, cost and user-friendly, and yield relatively high quantities of human skeletal muscle tissues. Additionally, since skeletal muscle plays an important functional role that is impaired over time in many disease states, an experimental platform for microtissue studies is most practical when minimally invasive calcium transient and contractile force measurements can be conducted directly within the platform itself. In this protocol, the fabrication of a 96-well platform known as 'MyoTACTIC', and en masse production of 3D human skeletal muscle microtissues (hMMTs) is described. In addition, the methods for a minimally invasive application of electrical stimulation that enables repeated measurements of skeletal muscle force and calcium handling of each microtissue over time are reported.

PMID:33682863 | DOI:10.3791/62307

Angew Chem Int Ed Engl. 2021 Mar 7. doi: 10.1002/anie.202100923. Online ahead of print.

ABSTRACT

We report the development of in vivo subcellular high-resolution mass spectrometry (HRMS) for proteo-metabolomic molecular systems biology in complex tissues. With light microscopy, we identified the left-dorsal and left-ventral animal cells in cleavage-stage non-sentient Xenopus laevis embryos. Using precision-translated fabricated microcapillaries, the subcellular content of each cell was double-probed, each time swiftly (<5 s/event) aspirating <5% of cell volume (~10 nL). The proteins and metabolites were analyzed by home-built ultrasensitive capillary electrophoresis electrospray ionization employing Orbitrap or time-of-flight HRMS. Label-free detection of ~150 metabolites (57 identified) and 738 proteins found proteo-metabolomic networks with differential quantitative activities between the cell types. With spatially and temporally scalable sampling, the technology preserved the integrity of the analyzed cells, the neighboring cells, and the embryo. 95% of the analyzed embryos developed into sentient tadpoles that were indistinguishable from their wild-type siblings based on anatomy and visual function in a background color preference assay.

PMID:33682213 | DOI:10.1002/anie.202100923

Genetics. 2021 Jan 23:iyab007. doi: 10.1093/genetics/iyab007. Online ahead of print.

ABSTRACT

In the last larval instar, uncommitted progenitor cells in the Drosophila eye primordium start to adopt individual retinal cell fates, arrest their growth and proliferation, and initiate terminal differentiation into photoreceptor neurons and other retinal cell types. To explore the regulation of these processes, we have performed mRNA-Seq studies of the larval eye and antennal primordial at multiple developmental stages. A total of 10,893 fly genes were expressed during these stages and could be adaptively clustered into gene groups, some of whose expression increases or decreases in parallel with the cessation of proliferation and onset of differentiation. Using in situ hybridization of a sample of 98 genes to verify spatial and temporal expression patterns, we estimate that 534 genes or more are transcriptionally upregulated during retinal differentiation, and 1367 or more downregulated as progenitor cells differentiate. Each group of co-expressed genes is enriched for regulatory motifs recognized by co-expressed transcription factors, suggesting that they represent coherent transcriptional regulatory programs. Using available mutant strains, we describe novel roles for the transcription factors SoxNeuro (SoxN), H6-like homeobox (Hmx), CG10253, without children (woc), Structure specific recognition protein (Ssrp), and multisex combs (mxc).

PMID:33681970 | DOI:10.1093/genetics/iyab007

Nat Cancer. 2021 Feb;2(2):141-156. doi: 10.1038/s43018-020-00159-4. Epub 2021 Jan 11.

ABSTRACT

The transcriptomic classification of glioblastoma (GBM) has failed to predict survival and therapeutic vulnerabilities. A computational approach for unbiased identification of core biological traits of single cells and bulk tumors uncovered four tumor cell states and GBM subtypes distributed along neurodevelopmental and metabolic axes, classified as proliferative/progenitor, neuronal, mitochondrial and glycolytic/plurimetabolic. Each subtype was enriched with biologically coherent multiomic features. Mitochondrial GBM was associated with the most favorable clinical outcome. It relied exclusively on oxidative phosphorylation for energy production, whereas the glycolytic/plurimetabolic subtype was sustained by aerobic glycolysis and amino acid and lipid metabolism. Deletion of the glucose-proton symporter SLC45A1 was the truncal alteration most significantly associated with mitochondrial GBM, and the reintroduction of SLC45A1 in mitochondrial glioma cells induced acidification and loss of fitness. Mitochondrial, but not glycolytic/plurimetabolic, GBM exhibited marked vulnerability to inhibitors of oxidative phosphorylation. The pathway-based classification of GBM informs survival and enables precision targeting of cancer metabolism.

PMID:33681822 | PMC:PMC7935068 | DOI:10.1038/s43018-020-00159-4

Front Mol Biosci. 2021 Feb 17;8:625979. doi: 10.3389/fmolb.2021.625979. eCollection 2021.

ABSTRACT

Ras oncoproteins play a crucial role in the onset, maintenance, and progression of the most common and deadly human cancers. Despite extensive research efforts, only a few mutant-specific Ras inhibitors have been reported. We show that cmp4-previously identified as a water-soluble Ras inhibitor- targets multiple steps in the activation and downstream signaling of different Ras mutants and isoforms. Binding of this pan-Ras inhibitor to an extended Switch II pocket on HRas and KRas proteins induces a conformational change that down-regulates intrinsic and GEF-mediated nucleotide dissociation and exchange and effector binding. A mathematical model of the Ras activation cycle predicts that the inhibitor severely reduces the proliferation of different Ras-driven cancer cells, effectively cooperating with Cetuximab to reduce proliferation even of Cetuximab-resistant cancer cell lines. Experimental data confirm the model prediction, indicating that the pan-Ras inhibitor is an appropriate candidate for medicinal chemistry efforts tailored at improving its currently unsatisfactory affinity.

PMID:33681292 | PMC:PMC7925909 | DOI:10.3389/fmolb.2021.625979