A statistical model for describing and simulating microbial community profiles

Many methods have been developed for statistical analysis of microbial community profiles, but due to the complex nature of typical microbiome measurements (e.g. sparsity, zero-inflation, non-independence, and compositionality) and of the associated underlying biology, it is difficult to compare or evaluate such methods within a single systematic framework. To address this challenge, we developed SparseDOSSA (Sparse Data Observations for the Simulation of Synthetic Abundances): a statistical model of microbial ecological population structure, which can be used to parameterize real-world microbial community profiles and to simulate new, realistic profiles of known structure for methods evaluation. Specifically, SparseDOSSA’s model captures marginal microbial feature abundances as a zero-inflated log-normal distribution, with additional model components for absolute cell counts and the sequence read generation process, microbe-microbe, and microbe-environment interactions. Together, these allow fully known covariance structure between synthetic features (i.e. “taxa”) or between features and “phenotypes” to be simulated for method benchmarking. Here, we demonstrate SparseDOSSA’s performance for 1) accurately modeling human-associated microbial population profiles; 2) generating synthetic communities with controlled population and ecological structures; 3) spiking-in true positive synthetic associations to benchmark analysis methods; and 4) recapitulating an end-to-end mouse microbiome feeding experiment. Together, these represent the most common analysis types in assessment of real microbial community environmental and epidemiological statistics, thus demonstrating SparseDOSSA’s utility as a general-purpose aid for modeling communities and evaluating quantitative methods. An open-source implementation is available at http://huttenhower.sph.harvard.edu/sparsedossa2.     

Future perspectives of energy saving down-flow hanging sponge (DHS) technology for wastewater valorization—a review

Reviews in Environmental Science and Bio/Technology - The down-flow hanging sponge (DHS) process has been rigorously studied as a significant post-treatment of anaerobically pretreated sewage and...     

High and low molecular weight hyaluronic acid differentially regulate human fibrocyte differentiation

Background

Following tissue injury, monocytes can enter the tissue and differentiate into fibroblast-like cells called fibrocytes, but little is known about what regulates this differentiation. Extracellular matrix contains high molecular weight hyaluronic acid (HMWHA; ∼2×10⁶ Da). During injury, HMWHA breaks down to low molecular weight hyaluronic acid (LMWHA; ∼0.8–8×10⁵ Da).

Methods and Findings

In this report, we show that HMWHA potentiates the differentiation of human monocytes into fibrocytes, while LMWHA inhibits fibrocyte differentiation. Digestion of HMWHA with hyaluronidase produces small hyaluronic acid fragments, and these fragments inhibit fibrocyte differentiation. Monocytes internalize HMWHA and LMWHA equally well, suggesting that the opposing effects on fibrocyte differentiation are not due to differential internalization of HMWHA or LMWHA. Adding HMWHA to PBMC does not appear to affect the levels of the hyaluronic acid receptor CD44, whereas adding LMWHA decreases CD44 levels. The addition of anti-CD44 antibodies potentiates fibrocyte differentiation, suggesting that CD44 mediates at least some of the effect of hyaluronic acid on fibrocyte differentiation. The fibrocyte differentiation-inhibiting factor serum amyloid P (SAP) inhibits HMWHA-induced fibrocyte differentiation and potentiates LMWHA-induced inhibition. Conversely, LMWHA inhibits the ability of HMWHA, interleukin-4 (IL-4), or interleukin-13 (IL-13) to promote fibrocyte differentiation.

Conclusions

We hypothesize that hyaluronic acid signals at least in part through CD44 to regulate fibrocyte differentiation, with a dominance hierarchy of SAP>LMWHA≥HMWHA>IL-4 or IL-13.     

Biomechanical Energy‐Driven Hybridized Generator as a Universal Portable Power Source for Smart/Wearable Electronics

The fast growth of smart electronics requires novel solutions to power them sustainably. Portable power sources capable of harvesting biomechanical energy are a promising modern approach to reduce battery dependency. Herein, a novel elastic impact‐based nonresonant hybridized generator (EINR‐HG) is reported to effectively harvest biomechanical energy from diverse human activities outdoors. Through the rational integration of a nonlinear electromagnetic generator with two contact‐mode triboelectric nanogenerators, the proposed EINR‐HG generates hybrid electrical output simultaneously under the same mechanical excitations. By introducing a flux‐concentrator with a nanowire‐nanofiber surface modification, significant improvement in the energy harvesting efficiency of the EINR‐HG is achieved. After optimizing using simulations and vibration tests, the as‐fabricated EINR‐HG delivers an outstanding normalized power density of 3.13 mW cm^?3 g^?2 across a matching resistance of 1.5 kΩ at 6 Hz under 1 g acceleration. Under human motion testing, the EINR‐HG generates an optimal output power of 131.4 mW with horizontal handshaking. With a customized power management circuit, the EINR‐HG serves as a universal power source that successfully drives commercial smart electronics, including smart bands and smartphones. This work shows the massive potential of biomechanical energy‐driven hybridized generators for powering personal electronics and portable healthcare monitoring devices.     

CCL20 Secretion from the Nucleus Pulposus Improves the Recruitment of CCR6-Expressing Th17 Cells to Degenerated IVD Tissues

Background

Studies elucidated that Th17 cells are important contributors to the pathogenesis of many immune-mediated diseases, and IL-17A is present in pathologic intervertebral disc (IVD) tissues. However, the mechanisms, how these cells traffic into the degenerate discs are not clear.

Materials and Methods

The samples collected from 53 patients had been divided into 3 groups: Group P (annulus fibrosus was intact), Group E (annulus fibrosus was reptured) and normal control. Immunohistochemistry was used to detect the expression of CCL20, CCR6, IL-17A, TNF–α and CD4 in IVD tissues. Moreover, nucleus pulposus (NP) cells had been cultured in the presence and absence of Th17 associated cytokines. The supernatants were detected for CCL20 concentrations by ELISA, and the NP cells for the expression of CCL20 mRNA. Additionally, peripheral blood (PB) samples had undergone detection for the expression of CCR6 mRNA and the proportion of IL-17-producing cells, including the surface expression of CCR6.

Results

Immunohistochemistry revealed that CCL20 and TNF-α were expressed in degenerated NP cells. Double-labeled immunofluorescence elaborated, IL-17-producing cells (CD4⁺IL-17A⁺ and CD4⁺CCR6⁺) appeared in the Group E samples, but no traces or expression in Group P and normal control. IL-17A and TNF-α, alone or combined, could enhance CCL20 secretion in a dose-dependent manner, which was obtained through RT-PCR results. There was a notable difference of CCR6 mRNA expression between patients and normal controls. In comparison to controls, flow cytometry data indicated that the proportion of IL-17-producing cells and the CCR6 expression in PB were significantly increased.

Conclusion

Our results provide a potential explanation for involvement of the CCL20-CCR6 system in the trafficking of IL-17-producing cells to degenerated IVD tissues. Additionally, our results explain the contribution of Th17 associated cytokines to the development of degenerated discs via the up-regulation of CCL20 secretion from NP cells, which forms a positive chemotactic feedback loop.     

The basis of antagonistic pleiotropy in hfq mutations that have opposite effects on fitness at slow and fast growth rates

Mutations beneficial in one environment may cause costs in different environments, resulting in antagonistic pleiotropy. Here, we describe a novel form of antagonistic pleiotropy that operates even within the same environment, where benefits and deleterious effects exhibit themselves at different growth rates. The fitness of hfq mutations in Escherichia coli affecting the RNA chaperone involved in small-RNA regulation is remarkably sensitive to growth rate. E. coli populations evolving in chemostats under nutrient limitation acquired beneficial mutations in hfq during slow growth (0.1 h⁻¹) but not in populations growing sixfold faster. Four identified hfq alleles from parallel populations were beneficial at 0.1 h⁻¹ and deleterious at 0.6 h⁻¹. The hfq mutations were beneficial, deleterious or neutral at an intermediate growth rate (0.5 h⁻¹) and one changed from beneficial to deleterious within a 36 min difference in doubling time. The benefit of hfq mutations was due to the greater transport of limiting nutrient, which diminished at higher growth rates. The deleterious effects of hfq mutations at 0.6 h⁻¹ were less clear, with decreased viability a contributing factor. The results demonstrate distinct pleiotropy characteristics in the alleles of the same gene, probably because the altered residues in Hfq affected the regulation of expression of different genes in distinct ways. In addition, these results point to a source of variation in experimental measurement of the selective advantage of a mutation; estimates of fitness need to consider variation in growth rate impacting on the magnitude of the benefit of mutations and on their fitness distributions.