The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models.

Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of 1,635 open-access datasets from four donors (∼30 tissues × âˆ¼15 assays). The datasets are mapped to matched, diploid genomes with long-read phasing and structural variants, instantiating a catalog of >1 million allele-specific loci. These loci exhibit coordinated activity along haplotypes and are less conserved than corresponding, non-allele-specific ones. Surprisingly, a deep-learning transformer model can predict the allele-specific activity based only on local nucleotide-sequence context, highlighting the importance of transcription-factor-binding motifs particularly sensitive to variants. Furthermore, combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci. It also enables models for transferring known eQTLs to difficult-to-profile tissues (e.g., from skin to heart). Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.

Soluble carbon source recovery using preconditioning coagulants for applicable short-term fermentation of waste activated sludge in WWTPs.

A huge production of waste activated sludge (WAS) has been a burden for wastewater treatment plants (WWTPs) with high disposal cost and little benefit back to wastewater purification. The short-chain fatty acids (SCFAs) produced by a short-term acidogenic fermentation of WAS before methane production have been proven to be a high-quality carbon source available for microbial denitrification process. The dual purpose of full recovery of fermentation liquid products and facilitating disposal of residual solid waste necessitate an efficient solid-liquid separation process of short-term fermentation liquid. The transformation and loss of various soluble carbon sources between solid and liquid are very important issues for carbon recovery efficiency when combining short-term fermentation and sludge dewatering in WWTPs. Here we testified the three conventional preconditioning coagulants, Polyferric Sulfate (PFS), Poly Aluminum Chloride (PAC) and Polyacrylamide (PAM), to improve the efficiency of subsequent solid-liquid separation. The results show that conversion yield of SCFAs in the liquid phase of sludge after short-term fermentation was 195 mg COD/g VSS, when using the coagulants PFS, PAC, and PAM for recovery, the recovery ratio was 79.5%, 82.0%, and 85.9%, respectively, while the dewaterability could be improved after preconditioning short-term fermentation sludge. The complexation of Al3+/Fe3+ in metal coagulants with carboxyl groups of SCFA demonstrated by Density Functional Theory calculation led to small part of soluble carbons co-migration to the solid phase, mainly a loss of high molecular weight organic compounds (carbohydrate, proteins, humic acids), while the application of PAM had little impact on carbon recovery. Economic calculations further showed PAM preconditioning short-term fermentation liquid of WAS could achieve higher recovery benefits.

Deep learning assisted plenoptic wavefront sensor for direct wavefront detection.

Traditional plenoptic wavefront sensors (PWFS) suffer from the obvious step change of the slope response, leading to poor wavefront detection performance. In order to solve this problem, in this paper, a deep learning model is proposed to restore phase maps directly from slope measurements of PWFS. Numerical simulations are employed to demonstrate our approach, and the statistical residual wavefront root mean square error (RMSE) of our method is 0.0810 ± 0.0258λ, which is much superior to those of modal algorithm (0.2511 ± 0.0587λ) and zonal approach (0.3584 ± 0.0487λ). The internal driving force of PWFS-ResUnet is investigated, and the slope response differences between sub-apertures and directions are considered as a probably key role to help our model to accurately restore the phase map. Additionally, the robustness of our model to turbulence strength and signal-to-noise ratio (SNR) level is also tested. The proposed method provides a new direction to solve the nonlinear problem of traditional PWFS.

Direct wavefront sensing with a plenoptic sensor based on deep learning.

Traditional plenoptic wavefront sensors (PWS) suffer from the obvious step change of the slope response which leads to the poor performance of phase retrieval. In this paper, a neural network model combining the transformer architecture with the U-Net model is utilized to restore wavefront directly from the plenoptic image of PWS. The simulation results show that the averaged root mean square error (RMSE) of residual wavefront is less than 1/14λ (Marechal criterion), proving the proposed method successfully breaks through the non-linear problem existed in PWS wavefront sensing. In addition, our model performs better than the recently developed deep learning models and traditional modal approach. Furthermore, the robustness of our model to turbulence strength and signal level is also tested, proving the good generalizability of our model. To the best of our knowledge, it is the first time to perform direct wavefront detection with a deep-learning-based method in PWS-based applications and achieve the state-of-the-art performance.

Effects of alkaline biochar on nitrogen transformation with fertilizer in agricultural soil.

The loss and negative impacts of nitrogen from fertilized soils remain a global challenge in agricultural field. Ammonium nitrogen (NH4+-N) and nitrate nitrogen (NO3--N) leaching, together with volatile ammonia loss are the main pathways of nitrogen loss. To improve nitrogen availability, alkaline biochar with improved adsorption capacities is a promising soil amendment. This study was objected to investigate the effects of alkaline biochar (ABC, pH 8.68) on nitrogen mitigation, the effects on nitrogen loss, and the interactions among the mixed soils (biochar, nitrogen fertilizer, and soil) under both pot and field experiments. From pot experiments, ABC addition resulted in the poor reservation of NH4+-N which converted to volatile NH3 under higher alkaline environments, mainly occurring in the first 3 days. But after, NO3--N could be largely retained in surface soil by ABC addition. The reservation of NO3--N by ABC offsets the loss of volatile NH3, and ABC ultimately showed positive reservations of nitrogen with fertilization. In the field experiment, the addition of urea inhibitor (UI) addition could inhibit the volatile NH3 loss caused by ABC mainly in the first week. The long-term operation demonstrated that ABC supported persistent effectiveness in reducing N loss, while UI treatment temporarily delayed the N loss through inhibition of fertilizer hydrolysis. Therefore, the addition of both ABC and UI contributed to reserve soil N in layers (0-50 cm) suitable for crop growth thus improving crops growth.

Correction: CTD: An information-theoretic algorithm to interpret sets of metabolomic and transcriptomic perturbations in the context of graphical models.

[This corrects the article DOI: 10.1371/journal.pcbi.1008550.].

CTD: An information-theoretic algorithm to interpret sets of metabolomic and transcriptomic perturbations in the context of graphical models.

We consider the following general family of algorithmic problems that arises in transcriptomics, metabolomics and other fields: given a weighted graph G and a subset of its nodes S, find subsets of S that show significant connectedness within G. A specific solution to this problem may be defined by devising a scoring function, the Maximum Clique problem being a classic example, where S includes all nodes in G and where the score is defined by the size of the largest subset of S fully connected within G. Major practical obstacles for the plethora of algorithms addressing this type of problem include computational efficiency and, particularly for more complex scores which take edge weights into account, the computational cost of permutation testing, a statistical procedure required to obtain a bound on the p-value for a connectedness score. To address these problems, we developed CTD, "Connect the Dots", a fast algorithm based on data compression that detects highly connected subsets within S. CTD provides information-theoretic upper bounds on p-values when S contains a small fraction of nodes in G without requiring computationally costly permutation testing. We apply the CTD algorithm to interpret multi-metabolite perturbations due to inborn errors of metabolism and multi-transcript perturbations associated with breast cancer in the context of disease-specific Gaussian Markov Random Field networks learned directly from respective molecular profiling data.

An Information-Theoretic Bound on p-Values for Detecting Communities Shared between Weighted Labeled Graphs.

Extraction of subsets of highly connected nodes ("communities" or modules) is a standard step in the analysis of complex social and biological networks. We here consider the problem of finding a relatively small set of nodes in two labeled weighted graphs that is highly connected in both. While many scoring functions and algorithms tackle the problem, the typically high computational cost of permutation testing required to establish the p-value for the observed pattern presents a major practical obstacle. To address this problem, we here extend the recently proposed CTD ("Connect the Dots") approach to establish information-theoretic upper bounds on the p-values and lower bounds on the size and connectedness of communities that are detectable. This is an innovation on the applicability of CTD, broadening its use to pairs of graphs.

IS26-mediated amplification of blaOXA-1 and blaCTX-M-15 with concurrent outer membrane porin disruption associated with de novo carbapenem resistance in a recurrent bacteraemia cohort.

BACKGROUND: Approximately half of clinical carbapenem-resistant Enterobacterales (CRE) isolates lack carbapenem-hydrolysing enzymes and develop carbapenem resistance through alternative mechanisms. OBJECTIVES: To elucidate development of carbapenem resistance mechanisms from clonal, recurrent ESBL-positive Enterobacterales (ESBL-E) bacteraemia isolates in a vulnerable patient population. METHODS: This study investigated a cohort of ESBL-E bacteraemia cases in Houston, TX, USA. Oxford Nanopore Technologies long-read and Illumina short-read sequencing data were used for comparative genomic analysis. Serial passaging experiments were performed on a set of clinical ST131 Escherichia coli isolates to recapitulate in vivo observations. Quantitative PCR (qPCR) and qRT-PCR were used to determine copy number and transcript levels of ß-lactamase genes, respectively. RESULTS: Non-carbapenemase-producing CRE (non-CP-CRE) clinical isolates emerged from an ESBL-E background through a concurrence of primarily IS26-mediated amplifications of blaOXA-1 and blaCTX-M-1 group genes coupled with porin inactivation. The discrete, modular translocatable units (TUs) that carried and amplified ß-lactamase genes mobilized intracellularly from a chromosomal, IS26-bound transposon and inserted within porin genes, thereby increasing ß-lactamase gene copy number and inactivating porins concurrently. The carbapenem resistance phenotype and TU-mediated ß-lactamase gene amplification were recapitulated by passaging a clinical ESBL-E isolate in the presence of ertapenem. Clinical non-CP-CRE isolates had stable carbapenem resistance phenotypes in the absence of ertapenem exposure. CONCLUSIONS: These data demonstrate IS26-mediated mechanisms underlying ß-lactamase gene amplification with concurrent outer membrane porin disruption driving emergence of clinical non-CP-CRE. Furthermore, these amplifications were stable in the absence of antimicrobial pressure. Long-read sequencing can be utilized to identify unique mobile genetic element mechanisms that drive antimicrobial resistance.

Clonal Emergence of Invasive Multidrug-Resistant Staphylococcus epidermidis Deconvoluted via a Combination of Whole-Genome Sequencing and Microbiome Analyses.

Background: Pathobionts, bacteria that are typically human commensals but can cause disease, contribute significantly to antimicrobial resistance. Staphylococcus epidermidis is a prototypical pathobiont as it is a ubiquitous human commensal but also a leading cause of healthcare-associated bacteremia. We sought to determine the etiology of a recent increase in invasive S. epidermidis isolates resistant to linezolid. Methods: Whole-genome sequencing (WGS) was performed on 176 S. epidermidis bloodstream isolates collected at the MD Anderson Cancer Center in Houston, Texas, between 2013 and 2016. Molecular relationships were assessed via complementary phylogenomic approaches. Abundance of the linezolid resistance determinant cfr was determined in stool samples via reverse-transcription quantitative polymerase chain reaction. Results: Thirty-nine of the 176 strains were linezolid resistant (22%). Thirty-one of the 39 linezolid-resistant S. epidermidis infections were caused by a particular clone resistant to multiple antimicrobials that spread among leukemia patients and carried cfr on a 49-kb plasmid (herein called pMB151a). The 6 kb of pMB151a surrounding the cfr gene was nearly 100% identical to a cfr-containing plasmid isolated from livestock-associated staphylococci in China. Analysis of serial stool samples from leukemia patients revealed progressive staphylococcal domination of the intestinal microflora and an increase in cfr abundance following linezolid use. Conclusions: The combination of linezolid use plus transmission of a multidrug-resistant clone drove expansion of invasive, linezolid-resistant S. epidermidis. Our results lend support to the notion that a combination of antibiotic stewardship plus infection control measures may help to control the spread of a multidrug-resistant pathobiont.

Comparison of retinal microvascular changes in eyes with high-tension glaucoma or normal-tension glaucoma: a quantitative optic coherence tomography angiographic study.

PURPOSE: The aim of this study is to determine and compare the changes in the retinal vasculature in eyes with high-tension glaucoma (HTG) or normal-tension glaucoma (NTG). METHODS: The right eyes of 43 HTG subjects, 33 NTG subjects, and 51 age- and sex-matched normal subjects were included in this cross-sectional study. Signals were projected from the internal limiting membrane to retinal pigment epithelium. The retinal perfused vessel densities in the peripapillary and parafoveal regions were measured automatically with optic coherence tomography angiography and the split-spectrum amplitude-decorrelation angiography algorithm. RESULTS: Compared with normal eyes, glaucomatous eyes had a smaller retinal nerve fibre layer (RNFL) thickness, smaller full parafoveal retinal thickness, and lower retinal perfused vessel density (PVD) in the peripapillary and parafoveal regions (all P < 0.01). The visual field, RNFL and retinal thicknesses, and PVD in the parafoveal region in the HTG eyes were similar to those in the NTG eyes. However, the NTG eyes had a significantly lower mean PVD than the HTG eyes in the peripapillary region. When the different sectors of the peripapillary region were studied, the difference was still significant in most sectors (all P < 0.05), except the inferotemporal sector (P = 0.676). CONCLUSIONS: The retinal perfused vessel density is significantly reduced in HTG and NTG eyes, and more prominently in the peripapillary region in NTG eyes.

Whole-Genome Sequencing Accurately Identifies Resistance to Extended-Spectrum ß-Lactams for Major Gram-Negative Bacterial Pathogens.

Background: There is marked interest in using DNA-based methods to detect antimicrobial resistance (AMR), with targeted polymerase chain reaction (PCR) approaches increasingly being incorporated into clinical care. Whole-genome sequencing (WGS) could offer significant advantages over targeted PCR for AMR detection, particularly for species where mutations are major drivers of AMR. Methods: Illumina MiSeq WGS and broth microdilution (BMD) assays were performed on 90 bloodstream isolates of the 4 most common gram-negative bacteria causing bloodstream infections in neutropenic patients. The WGS data, including both gene presence/absence and detection of mutations in an array of AMR-relevant genes, were used to predict resistance to 4 ß-lactams commonly used in the empiric treatment of neutropenic fever. The genotypic predictions were then compared to phenotypic resistance as determined by BMD and by commercial methods during routine patient care. Results: Of 133 putative instances of resistance to the ß-lactams of interest identified by WGS, only 87 (65%) would have been detected by a typical PCR-based approach. The sensitivity, specificity, and positive and negative predictive values for WGS in predicting AMR were 0.87, 0.98, 0.97, and 0.91, respectively. Using BMD as the gold standard, our genotypic resistance prediction approach had a significantly higher positive predictive value compared to minimum inhibitory concentrations generated by commercial methods (0.97 vs 0.92; P = .025). Conclusions: These data demonstrate the potential feasibility of using WGS to guide antibiotic treatment decisions for patients with life-threatening infections for an array of medically important pathogens.

Improving Retinal Image Quality Using Registration with an SIFT Algorithm in Quasi-Confocal Line Scanning Ophthalmoscope.

When high-magnification images are taken with a quasi-confocal line scanning ophthalmoscope (LSO), the quality of images always suffers from Gaussian noise, and the signal to noise ratio (SNR) is very low for a safer laser illumination. In addition, motions of the retina severely affect the stabilization of the real-time video resulting in significant distortions or warped images. We describe a scale-invariant feature transform (SIFT) algorithm to automatically abstract corner points with subpixel resolution and match these points in sequential images using an affine transformation. Once n images are aligned and averaged, the noise level drops by a factor of [Formula: see text] and the image quality is improved. The improvement of image quality is independent of the acquisition method as long as the image is not warped, particularly severely during confocal scanning. Consequently, even better results can be expected by implementing this image processing technique on higher resolution images.

Optical Design of Adaptive Optics Confocal Scanning Laser Ophthalmoscope with Two Deformable Mirrors.

We describe the optical design of a confocal scanning laser ophthalmoscope with two deformable mirrors. Spherical mirrors are used for pupil relay. Defocus aberration of the human eye is corrected by a Badal focusing structure and astigmatism aberration is corrected by a deformable mirror. The main optical system achieves a diffraction-limited performance through the entire scanning field (6 mm pupil, 3 degrees on pupil plane). The performance of the optical system, with correction of defocus and astigmatism, is also evaluated.

Design of a Compact, Bimorph Deformable Mirror-Based Adaptive Optics Scanning Laser Ophthalmoscope.

We have designed, constructed and tested an adaptive optics scanning laser ophthalmoscope (AOSLO) using a bimorph mirror. The simulated AOSLO system achieves diffraction-limited criterion through all the raster scanning fields (6.4 mm pupil, 3° × 3° on pupil). The bimorph mirror-based AOSLO corrected ocular aberrations in model eyes to less than 0.1 µm RMS wavefront error with a closed-loop bandwidth of a few Hz. Facilitated with a bimorph mirror at a stroke of ±15 µm with 35 elements and an aperture of 20 mm, the new AOSLO system has a size only half that of the first-generation AOSLO system. The significant increase in stroke allows for large ocular aberrations such as defocus in the range of ±600° and astigmatism in the range of ±200°, thereby fully exploiting the AO correcting capabilities for diseased human eyes in the future.

Volatile fatty acids bio-production using extracellular polymeric substances disengaged from sludge for carbon source recycling.

Excessive waste-activated sludge (WAS) and insufficient carbon source (CS) for biological nitrogen removal (BNR) often coexist in municipal sewage treatment. Although the production of volatile fatty acids (VFAs) from WAS has been recognized as a promising solution, the development is limited by low VFAs production efficiency and dewatering deterioration of sludge. This study extracted the extracellular polymeric substances (EPS) from sludge by low-temperature thermal-hydrolysis (LTH) and high-speed hydro-cyclone (HSHC) pretreatment and recovered it for high-quality VFAs bio-production in thermophilic fermentation. Microbial mechanism analysis disclosed that interspecific interaction networks composed of functional flora, which accumulate VFAs by bio-converting EPS primarily and supplemented by EPS synthesis, guaranteed the efficient bio-production of VFAs. This process scheme shows promise in providing alternative denitrification CSs and avoiding deterioration of sludge dewaterability.

Study of natural attenuation after acid in situ leaching of uranium mines using isotope fractionation and geochemical data.

Acid in situ leaching (AISL) is a subsurface mining approach suitable for low-grade ores which does not generate tailings, and has been adopted widely in uranium mining. However, this technique causes an extremely high concentration of contaminants at post-mining sites and in the surroundings soon after the mining ceases. As a potential AISL remediation strategy, natural attenuation has not been studied in detail. To address this problem, groundwater collected from 26 wells located within, adjacent, upgradient, and downgradient of a post-mining site were chosen to analyze the fate of U(VI), SO42-, δ34S, and δ238U, to reveal the main mechanisms governing the migration and attenuation of the dominant contaminants and the spatio-temporal evolutions of contaminants in the confined aquifer of the post-mining site. The δ238U values vary from -0.07 ‰ to 0.09 ‰ in the post-mining site and from -1.43 ‰ to 0.03 ‰ around the post-mining site. The δ34S values were found to vary from 3.3 ‰ to 6.2 ‰ in the post-mining site and from 6.0 ‰ to 11.0 ‰ around the post-mining site. Detailed analysis suggests that there are large differences between the range of isotopic composition variation and the range of pollutants concentration distribution, and the estimated Rayleigh isotope fractionation factor is 0.9994-0.9997 for uranium and 1.0032-1.0061 for sulfur. The isotope ratio of uranium and sulfur can be used to deduce the migration history of the contaminants and the irreversibility of the natural attenuation process in the anoxic confined aquifer. Combining the isotopic fractionation data for U and S with the concentrations of uranium and sulfate improved the accuracy of understanding of reducing conditions along the flow path. The study also indicated that as long as the geological conditions are favorable for redox reactions, natural attenuation could be used as a cost-effective remediation scheme.

Carbon source recovery from waste sludge reduces greenhouse gas emissions in a pilot-scale industrial wastewater treatment plant.

Carbon cycle regulation and greenhouse gas (GHG) emission abatement within wastewater treatment plants (WWTPs) can theoretically improve sustainability. Currently, however, large amounts of external carbon sources used for deep nitrogen removal and waste sludge disposal aggravate the carbon footprint of most WWTPs. In this pilot-scale study, considerable carbon was preliminarily recovered from primary sludge (PS) through short-term (five days) acidogenic fermentation and subsequently utilized on-site for denitrification in a wool processing industrial WWTP. The recovered sludge-derived carbon sources were excellent electron donors that could be used as additional carbon supplements for commercial glucose to enhance denitrification. Additionally, improvements in carbon and nitrogen flow further contributed to GHG emission abatement. Overall, a 9.1% reduction in sludge volatile solids was achieved from carbon recovery, which offset 57.4% of external carbon sources, and the indirect GHG emissions of the target industrial WWTP were reduced by 8.05%. This study demonstrates that optimizing the allocation of carbon mass flow within a WWTP has numerous benefits.

Untargeted Metabolomics of Slc13a5 Deficiency Reveal Critical Liver-Brain Axis for Lipid Homeostasis.

Though biallelic variants in SLC13A5 are known to cause severe encephalopathy, the mechanism of this disease is poorly understood. SLC13A5 protein deficiency reduces citrate transport into the cell. Downstream abnormalities in fatty acid synthesis and energy generation have been described, though biochemical signs of these perturbations are inconsistent across SLC13A5 deficiency patients. To investigate SLC13A5-related disorders, we performed untargeted metabolic analyses on the liver, brain, and serum from a Slc13a5-deficient mouse model. Metabolomic data were analyzed using the connect-the-dots (CTD) methodology and were compared to plasma and CSF metabolomics from SLC13A5-deficient patients. Mice homozygous for the Slc13a5tm1b/tm1b null allele had perturbations in fatty acids, bile acids, and energy metabolites in all tissues examined. Further analyses demonstrated that for several of these molecules, the ratio of their relative tissue concentrations differed widely in the knockout mouse, suggesting that deficiency of Slc13a5 impacts the biosynthesis and flux of metabolites between tissues. Similar findings were observed in patient biofluids, indicating altered transport and/or flux of molecules involved in energy, fatty acid, nucleotide, and bile acid metabolism. Deficiency of SLC13A5 likely causes a broader state of metabolic dysregulation than previously recognized, particularly regarding lipid synthesis, storage, and metabolism, supporting SLC13A5 deficiency as a lipid disorder.

Integrated constructed wetland and bioelectrochemistry system approach for simultaneous enhancment of p-chloronitrobenzene and nitrogen transformations performance.

Constructed wetlands (CWs) integrated with the bioelectrochemical system (BES-CW) to stimulate bio-refractory compounds removal holds particular promise, owing to its inherent greater scale and well-recognized environmentally benign wastewater advanced purification technology. However, the knowledge regarding the feasibility and removal mechanisms, particularly the potential negative effects of biorefractory compounds on nitrogen removal performance for the CWs is far insufficient. This study performed a critical assessment by using BES-CW (ECW) and conventional CW (CW) to investigate the effects of p-Chloronitrobenzene (pCNB) on nitrogen transformations in CWs. The results showed that low concentration (1 mg·L-1) of pCNB would inhibit the ammonia oxidation in CWs, while ECW could improve its tolerance to pCNB to a certain level (8 mg·L-1) due to the high pCNB degradation efficiencies (2.5 times higher than CWs), accordingly, much higher TN and nitrate removal efficiencies were observed in ECWs, 81.71% - 96.82% (TN) higher than CWs, further leading to a lower N2O emission from ECWs than CWs. The main intermediate of pCNB degradation was p-Chloroaniline (pCAN) and the genera Geobacter and Propionimicrobium were consider to be the responsible pCNB degradation bacteria in the present study. However, too high concentration (20 mg·L-1) of pCNB would have a huge impact on ECW and CW, especially microbial biomass. Nevertheless, ECW could improve the 1.87 times higher microbial biomass than CW on the substrate. Accordingly, considerably higher functional gene abundance was observed in ECW. Therefore, the introduction of BES has great potential to ensure CW stability when treating industrial wastewater containing bio-refractory compounds.