Patterns and Scales in Gastrointestinal Microbial Ecology

The body surfaces of humans and other animals are colonized at birth by microorganisms. The majority of microbial residents on the human body exist within gastrointestinal (GI) tract communities, where they contribute to many aspects of host biology and pathobiology. Recent technological advances have expanded our ability to perceive the membership and physiologic traits of microbial communities along the GI tract. To translate this information into a mechanistic and practical understanding of host-microbe and microbe-microbe relationships, it is necessary to recast our conceptualization of the GI tract and its resident microbial communities in ecological terms. This review depicts GI microbial ecology in the context of 2 fundamental ecological concepts: (1) the patterns of biodiversity within the GI tract and (2) the scales of time, space, and environment within which we perceive those patterns. We show how this conceptual framework can be used to integrate our existing knowledge and identify important open questions in GI microbial ecology

Characterization of RNA content in individual phase-separated coacervate microdroplets

Liquid-liquid phase separation or condensation is a form of macromolecular compartmentalization. Condensates formed by complex coacervation were hypothesized to have played a crucial part during the origin-of-life. In living cells, condensation organizes biomolecules into a wide range of membraneless compartments. Although RNA is a key component of condensation in cells and the central component of the RNA world hypothesis, little is known about what determines RNA accumulation in condensates and how single condensates differ in their RNA composition. Therefore, we developed an approach to read the RNA content from single condensates using high-throughput sequencing. We find that RNAs which are enriched for specific sequence motifs efficiently accumulate in condensates. These motifs show high sequence similarity to short interspersed elements (SINEs). We observed similar results for protein-derived condensates, demonstrating applicability across different in vitro reconstituted membraneless organelles. Thus, our results provide a new inroad to explore the RNA content of phase-separated droplets at single condensate resolution.Competing Interest StatementThe authors have declared no competing interest

Dipolar interactions, molecular flexibility, and flexoelectricity in bent-core liquid crystals

The effects of dipolar interactions and molecular flexibility on the structure and phase behavior of bent-core molecular fluids are studied using Monte Carlo computer simulations. Some calculations of flexoelectric coefficients are also reported. The rigid cores of the model molecules consist of either five or seven soft spheres arranged in a `V' shape with external bend angle $\gamma$. With purely repulsive sphere-sphere interactions and $\gamma=0^\circ$ (linear molecules) the seven-sphere model exhibits isotropic, uniaxial nematic, smectic-A, and tilted phases. With $\gamma \geq 20^\circ$ the smectic-A phase disappears, while the system with $\gamma \geq 40^\circ$ shows a direct tilted smectic--isotropic fluid transition. The addition of electrostatic interactions between transverse dipole moments on the apical spheres is generally seen to reduce the degree of tilt in the smectic and solid phases, destabilize the nematic and smectic-A phases of linear molecules, and destabilize the tilted smectic-B phase of bent-core molecules. The effects of adding three-segment flexible tails to the ends of five-sphere bent-core molecules are examined using configurational-bias Monte Carlo simulations. Only isotropic and smectic phases are observed. On the one hand, molecular flexibility gives rise to pronounced fluctuations in the smectic-layer structure, bringing the simulated system in better correspondence with real materials; on the other hand, the smectic phase shows almost no tilt. Lastly, the flexoelectric coefficients of various nematic phases -- with and without attractive sphere-sphere interactions -- are presented. The results are encouraging, but the computational effort required is a drawback associated with the use of fluctuation relations.Comment: 11 pages, 9 figure

High-throughput muscle fiber typing from RNA sequencing data

Background: Skeletal muscle fiber type distribution has implications for human health, muscle function, and performance. This knowledge has been gathered using labor-intensive and costly methodology that limited these studies. Here, we present a method based on muscle tissue RNA sequencing data (totRNAseq) to estimate the distribution of skeletal muscle fiber types from frozen human samples, allowing for a larger number of individuals to be tested. Methods: By using single-nuclei RNA sequencing (snRNAseq) data as a reference, cluster expression signatures were produced by averaging gene expression of cluster gene markers and then applying these to totRNAseq data and inferring muscle fiber nuclei type via linear matrix decomposition. This estimate was then compared with fiber type distribution measured by ATPase staining or myosin heavy chain protein isoform distribution of 62 muscle samples in two independent cohorts (n = 39 and 22). Results: The correlation between the sequencing-based method and the other two were r(ATpas) = 0.44 [0.13-0.67], [95% CI], and r(myosin) = 0.83 [0.61-0.93], with p = 5.70 x 10(-3) and 2.00 x 10(-6), respectively. The deconvolution inference of fiber type composition was accurate even for very low totRNAseq sequencing depths, i.e., down to an average of similar to 10,000 paired-end reads. Conclusions: This new method (https://github.com/OlaHanssonLab/PredictFiberType) consequently allows for measurement of fiber type distribution of a larger number of samples using totRNAseq in a cost and labor-efficient way. It is now feasible to study the association between fiber type distribution and e.g. health outcomes in large well-powered studies.Peer reviewe

High-throughput muscle fiber typing from RNA sequencing data

Background Skeletal muscle fiber type distribution has implications for human health, muscle function, and performance. This knowledge has been gathered using labor-intensive and costly methodology that limited these studies. Here, we present a method based on muscle tissue RNA sequencing data (totRNAseq) to estimate the distribution of skeletal muscle fiber types from frozen human samples, allowing for a larger number of individuals to be tested. Methods By using single-nuclei RNA sequencing (snRNAseq) data as a reference, cluster expression signatures were produced by averaging gene expression of cluster gene markers and then applying these to totRNAseq data and inferring muscle fiber nuclei type via linear matrix decomposition. This estimate was then compared with fiber type distribution measured by ATPase staining or myosin heavy chain protein isoform distribution of 62 muscle samples in two independent cohorts (n = 39 and 22). Results The correlation between the sequencing-based method and the other two were rATPas = 0.44 [0.13–0.67], [95% CI], and rmyosin = 0.83 [0.61–0.93], with p = 5.70 × 10–3 and 2.00 × 10–6, respectively. The deconvolution inference of fiber type composition was accurate even for very low totRNAseq sequencing depths, i.e., down to an average of ~ 10,000 paired-end reads. Conclusions This new method (https://github.com/OlaHanssonLab/PredictFiberType) consequently allows for measurement of fiber type distribution of a larger number of samples using totRNAseq in a cost and labor-efficient way. It is now feasible to study the association between fiber type distribution and e.g. health outcomes in large well-powered studies.journal articl

Microbiota modulate transcription in the intestinal epithelium without remodeling the accessible chromatin landscape

Microbiota regulate intestinal physiology by modifying host gene expression along the length of the intestine, but the underlying regulatory mechanisms remain unresolved. Transcriptional specificity occurs through interactions between transcription factors (TFs) and cis-regulatory regions (CRRs) characterized by nucleosome-depleted accessible chromatin. We profiled transcriptome and accessible chromatin landscapes in intestinal epithelial cells (IECs) from mice reared in the presence or absence of microbiota. We show that regional differences in gene transcription along the intestinal tract were accompanied by major alterations in chromatin accessibility. Surprisingly, we discovered that microbiota modify host gene transcription in IECs without significantly impacting the accessible chromatin landscape. Instead, microbiota regulation of host gene transcription might be achieved by differential expression of specific TFs and enrichment of their binding sites in nucleosome-depleted CRRs near target genes. Our results suggest that the chromatin landscape in IECs is preprogrammed by the host in a region-specific manner to permit responses to microbiota through binding of open CRRs by specific TFs

Search for Gravitational Wave Bursts from Soft Gamma Repeaters

We present the results of a LIGO search for short-duration gravitational waves (GWs) associated with Soft Gamma Repeater (SGR) bursts. This is the first search sensitive to neutron star f-modes, usually considered the most efficient GW emitting modes. We find no evidence of GWs associated with any SGR burst in a sample consisting of the 27 Dec. 2004 giant flare from SGR 1806-20 and 190 lesser events from SGR 1806-20 and SGR 1900+14 which occurred during the first year of LIGO's fifth science run. GW strain upper limits and model-dependent GW emission energy upper limits are estimated for individual bursts using a variety of simulated waveforms. The unprecedented sensitivity of the detectors allows us to set the most stringent limits on transient GW amplitudes published to date. We find upper limit estimates on the model-dependent isotropic GW emission energies (at a nominal distance of 10 kpc) between 3x10^45 and 9x10^52 erg depending on waveform type, detector antenna factors and noise characteristics at the time of the burst. These upper limits are within the theoretically predicted range of some SGR models.Comment: 6 pages, 1 Postscript figur

First LIGO search for gravitational wave bursts from cosmic (super)strings

We report on a matched-filter search for gravitational wave bursts from cosmic string cusps using LIGO data from the fourth science run (S4) which took place in February and March 2005. No gravitational waves were detected in 14.9 days of data from times when all three LIGO detectors were operating. We interpret the result in terms of a frequentist upper limit on the rate of gravitational wave bursts and use the limits on the rate to constrain the parameter space (string tension, reconnection probability, and loop sizes) of cosmic string models.Comment: 11 pages, 3 figures. Replaced with version submitted to PR

All-sky LIGO Search for Periodic Gravitational Waves in the Early S5 Data

We report on an all-sky search with the LIGO detectors for periodic gravitational waves in the frequency range 50--1100 Hz and with the frequency's time derivative in the range -5.0E-9 Hz/s to zero. Data from the first eight months of the fifth LIGO science run (S5) have been used in this search, which is based on a semi-coherent method (PowerFlux) of summing strain power. Observing no evidence of periodic gravitational radiation, we report 95% confidence-level upper limits on radiation emitted by any unknown isolated rotating neutron stars within the search range. Strain limits below 1.E-24 are obtained over a 200-Hz band, and the sensitivity improvement over previous searches increases the spatial volume sampled by an average factor of about 100 over the entire search band. For a neutron star with nominal equatorial ellipticity of 1.0E-6, the search is sensitive to distances as great as 500 pc--a range that could encompass many undiscovered neutron stars, albeit only a tiny fraction of which would likely be rotating fast enough to be accessible to LIGO. This ellipticity is at the upper range thought to be sustainable by conventional neutron stars and well below the maximum sustainable by a strange quark star.Comment: 6 pages, 1 figur

Search for gravitational waves from binary inspirals in S3 and S4 LIGO data

We report on a search for gravitational waves from the coalescence of compact binaries during the third and fourth LIGO science runs. The search focused on gravitational waves generated during the inspiral phase of the binary evolution. In our analysis, we considered three categories of compact binary systems, ordered by mass: (i) primordial black hole binaries with masses in the range 0.35 M(sun) < m1, m2 < 1.0 M(sun), (ii) binary neutron stars with masses in the range 1.0 M(sun) < m1, m2 < 3.0 M(sun), and (iii) binary black holes with masses in the range 3.0 M(sun)< m1, m2 < m_(max) with the additional constraint m1+ m2 < m_(max), where m_(max) was set to 40.0 M(sun) and 80.0 M(sun) in the third and fourth science runs, respectively. Although the detectors could probe to distances as far as tens of Mpc, no gravitational-wave signals were identified in the 1364 hours of data we analyzed. Assuming a binary population with a Gaussian distribution around 0.75-0.75 M(sun), 1.4-1.4 M(sun), and 5.0-5.0 M(sun), we derived 90%-confidence upper limit rates of 4.9 yr^(-1) L10^(-1) for primordial black hole binaries, 1.2 yr^(-1) L10^(-1) for binary neutron stars, and 0.5 yr^(-1) L10^(-1) for stellar mass binary black holes, where L10 is 10^(10) times the blue light luminosity of the Sun.Comment: 12 pages, 11 figure