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Microbial communities in the liver and brain are informative for postmortem submersion interval estimation in the late phase of decomposition: A study in mouse cadavers recovered from freshwater

Introduction Bodies recovered from water, especially in the late phase of decomposition, pose difficulties to the investigating authorities. Various methods have been proposed for postmortem submersion interval (PMSI) estimation and drowning identification, but some limitations remain. Many recent studies have proved the value of microbiota succession in viscera for postmortem interval estimation. Nevertheless, the visceral microbiota succession and its application for PMSI estimation and drowning identification require further investigation. Methods In the current study, mouse drowning and CO 2 asphyxia models were developed, and cadavers were immersed in freshwater for 0 to 14 days. Microbial communities in the liver and brain were characterized via 16S rDNA high-throughput sequencing. Results Only livers and brains collected from 5 to 14 days postmortem were qualified for sequencing. There was significant variation between microbiota from liver and brain. Differences in microbiota between the cadavers of mice that had drowned and those only subjected to postmortem submersion decreased over the PMSI. Significant successions in microbial communities were observed among the different subgroups within the late phase of the PMSI in livers and brains. Eighteen taxa in the liver which were mainly related to Clostridium_sensu_stricto and Aeromonas , and 26 taxa in the brain which were mainly belonged to Clostridium_sensu_stricto , Acetobacteroides , and Limnochorda , were selected as potential biomarkers for PMSI estimation based on a random forest algorithm. The PMSI estimation models established yielded accurate prediction results with mean absolute errors ± the standard error of 1.282 ± 0.189 d for the liver and 0.989 ± 0.237 d for the brain. Conclusions The present study provides novel information on visceral postmortem microbiota succession in corpses submerged in freshwater which sheds new light on PMSI estimation based on the liver and brain in forensic practice.

Wang, Linlin↗

Nucleosomes Shape DNA Polymorphism and Divergence

An estimated 80% of genomic DNA in eukaryotes is packaged as nucleosomes, which, together with the remaining interstitial linker regions, generate higher order chromatin structures. Nucleosome sequences isolated from diverse organisms exhibit ,10 bp periodic variations in AA, TT and GC dinucleotide frequencies. These sequence elements generate intrinsically curved DNA and help establish the histone-DNA interface. We investigated an important unanswered question concerning the interplay between chromatin organization and genome evolution: do the DNA sequence preferences inherent to the highly conserved histone core exert detectable natural selection on genomic divergence and polymorphism? To address this hypothesis, we isolated nucleosomal DNA sequences from Drosophila melanogaster embryos and examined the underlying genomic variation within and between species. We found that divergence along the D. melanogaster lineage is periodic across nucleosome regions with base changes following preferred nucleotides, providing new evidence for systematic evolutionary forces in the generation and maintenance of nucleosome-associated dinucleotide periodicities. Further, Single Nucleotide Polymorphism (SNP) frequency spectra show striking periodicities across nucleosomal regions, paralleling divergence patterns. Preferred alleles occur at higher frequencies in natural populations, consistent with a central role for natural selection. These patterns are stronger for nucleosomes in introns than in intergenic regions, suggesting selection is stronger in transcribed regions where nucleosomes undergo more displacement, remodeling and functional modification. In addition, we observe a large-scale (~180 bp) periodic enrichment of AA/TT dinucleotides associated with nucleosome occupancy, while GC dinucleotide frequency peaks in linker regions. Divergence and polymorphism data also support a role for natural selection in the generation and maintenance of these super-nucleosomal patterns. Our results demonstrate that nucleosome-associated sequence periodicities are under selective pressure, implying that structural interactions between nucleosomes and DNA sequence shape sequence evolution, particularly in introns.

59 BASIC BIOLOGICAL SCIENCES↗

Sequence-Mandated, Distinct Assembly of Giant Molecules

Although controlling the primary structure of synthetic polymers is itself a great challenge, the potential of sequence control for tailoring hierarchical structures remains to be exploited, especially in the creation of new and unconventional phases. A series of model amphiphilic chain-like giant molecules was designed and synthesized by interconnecting both hydrophobic and hydrophilic molecular nanoparticles in precisely defined sequence and composition to investigate their sequence-dependent phase structures. Not only compositional variation changed the self-assembled supramolecular phases, but also specific sequences induce unconventional phase formation, including Frank-Kasper phases. The formation mechanism was attributed to the conformational change driven by the collective hydrogen bonding and the sequence-mandated topology of the molecules. Lastly, these results show that sequence control in synthetic polymers can have a dramatic impact on polymer properties and self-assembly.

36 MATERIALS SCIENCE↗

High phenotypic and genotypic plasticity among strains of the mushroom-forming fungus Schizophyllum commune

Schizophyllum commune is a mushroom-forming fungus notable for its distinctive fruiting bodies with split gills. It is used as a model organism to study mushroom development, lignocellulose degradation and mating type loci. It is a hypervariable species with considerable genetic and phenotypic diversity between the strains. In this study, we systematically phenotyped 16 dikaryotic strains for aspects of mushroom development and 18 monokaryotic strains for lignocellulose degradation. There was considerable heterogeneity among the strains regarding these phenotypes. The majority of the strains developed mushrooms with varying morphologies, although some strains only grew vegetatively under the tested conditions. Growth on various carbon sources showed strain-specific profiles. The genomes of seven monokaryotic strains were sequenced and analyzed together with six previously published genome sequences. Moreover, the related species Schizophyllum fasciatum was sequenced. Although there was considerable genetic variation between the genome assemblies, the genes related to mushroom formation and lignocellulose degradation were well conserved. These sequenced genomes, in combination with the high phenotypic diversity, will provide a solid basis for functional genomics analyses of the strains of S. commune.

59 BASIC BIOLOGICAL SCIENCES↗

classLog: Logistic regression for the classification of genetic sequences

Introduction Sequencing and phylogenetic classification have become a common task in human and animal diagnostic laboratories. It is routine to sequence pathogens to identify genetic variations of diagnostic significance and to use these data in realtime genomic contact tracing and surveillance. Under this paradigm, unprecedented volumes of data are generated that require rapid analysis to provide meaningful inference. Methods We present a machine learning logistic regression pipeline that can assign classifications to genetic sequence data. The pipeline implements an intuitive and customizable approach to developing a trained prediction model that runs in linear time complexity, generating accurate output rapidly, even with incomplete data. Our approach was benchmarked against porcine respiratory and reproductive syndrome virus (PRRSv) and swine H1 influenza A virus (IAV) datasets. Trained classifiers were tested against sequences and simulated datasets that artificially degraded sequence quality at 0, 10, 20, 30, and 40%. Results When applied to a poor-quality sequence data, the classifier achieved between >85% to 95% accuracy for the PRRSv and the swine H1 IAV HA dataset and this increased to near perfect accuracy when using the full dataset. The model also identifies amino acid positions used to determine genetic clade identity through a feature selection ranking within the model. These positions can be mapped onto a maximum-likelihood phylogenetic tree, allowing for the inference of clade defining mutations. Discussion Our approach is implemented as a python package with code available at https://github.com/flu-crew/classLog .

Zeller, Michael A.↗

Noise resilience of variational quantum compiling

Variational hybrid quantum-classical algorithms (VHQCAs) are near-term algorithms that leverage classical optimization to minimize a cost function, which is efficiently evaluated on a quantum computer. Recently VHQCAs have been proposed for quantum compiling, where a target unitary U is compiled into a short-depth gate sequence V. In this work, we report on a surprising form of noise resilience for these algorithms. Namely, we find one often learns the correct gate sequence V (i.e. the correct variational parameters) despite various sources of incoherent noise acting during the cost-evaluation circuit. Our main results are rigorous theorems stating that the optimal variational parameters are unaffected by a broad class of noise models, such as measurement noise, gate noise, and Pauli channel noise. Furthermore, our numerical implementations on IBM's noisy simulator demonstrate resilience when compiling the quantum Fourier transform, Toffoli gate, and W-state preparation. Hence, variational quantum compiling, due to its robustness, could be practically useful for noisy intermediate-scale quantum devices. Finally, we speculate that this noise resilience may be a general phenomenon that applies to other VHQCAs such as the variational quantum eigensolver.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Genome Variations Associated with Viral Susceptibility and Calcification in Emiliania huxleyi

Emiliania huxleyi, a key player in the global carbon cycle is one of the best studied coccolithophores with respect to biogeochemical cycles, climatology, and host-virus interactions. Strains of E. huxleyi show phenotypic plasticity regarding growth behaviour, light-response, calcification, acidification, and virus susceptibility. This phenomenon is likely a consequence of genomic differences, or transcriptomic responses, to environmental conditions or threats such as viral infections. We used an E. huxleyi genome microarray based on the sequenced strain CCMP1516 (reference strain) to perform comparative genomic hybridizations (CGH) of 16 E. huxleyi strains of different geographic origin. We investigated the genomic diversity and plasticity and focused on the identification of genes related to virus susceptibility and coccolith production (calcification). Among the tested 31940 gene models a core genome of 14628 genes was identified by hybridization among 16 E. huxleyi strains. 224 probes were characterized as specific for the reference strain CCMP1516. Compared to the sequenced E. huxleyi strain CCMP1516 variation in gene content of up to 30 percent among strains was observed. Comparison of core and non-core transcripts sets in terms of annotated functions reveals a broad, almost equal functional coverage over all KOG-categories of both transcript sets within the whole annotated genome. Within the variable (non-core) genome we identified genes associated with virus susceptibility and calcification. Genes associated with virus susceptibility include a Bax inhibitor-1 protein, three LRR receptor-like protein kinases, and mitogen-activated protein kinase. Our list of transcripts associated with coccolith production will stimulate further research, e.g. by genetic manipulation. In particular, the V-type proton ATPase 16 kDa proteolipid subunit is proposed to be a plausible target gene for further calcification studies.

59 BASIC BIOLOGICAL SCIENCES↗

Estimating nonrigid motion from inconsistent intensity with robust shape features

Purpose: To develop a nonrigid motion estimation method that is robust to heterogeneous intensity inconsistencies amongst the image pairs or image sequence. Methods: Intensity and contrast variations, as in dynamic contrast enhanced magnetic resonance imaging, present a considerable challenge to registration methods based on general discrepancy metrics. In this study, the authors propose and validate a novel method that is robust to such variations by utilizing shape features. The geometry of interest (GOI) is represented with a flexible zero level set, segmented via well-behaved regularized optimization. The optimization energy drives the zero level set to high image gradient regions, and regularizes it with area and curvature priors. The resulting shape exhibits high consistency even in the presence of intensity or contrast variations. Subsequently, a multiscale nonrigid registration is performed to seek a regular deformation field that minimizes shape discrepancy in the vicinity of GOIs. Results: To establish the working principle, realistic 2D and 3D images were subject to simulated nonrigid motion and synthetic intensity variations, so as to enable quantitative evaluation of registration performance. The proposed method was benchmarked against three alternative registration approaches, specifically, optical flow, B-spline based mutual information, and multimodality demons. When intensity consistency was satisfied, all methods had comparable registration accuracy for the GOIs. When intensities among registration pairs were inconsistent, however, the proposed method yielded pronounced improvement in registration accuracy, with an approximate fivefold reduction in mean absolute error (MAE = 2.25 mm, SD = 0.98 mm), compared to optical flow (MAE = 9.23 mm, SD = 5.36 mm), B-spline based mutual information (MAE = 9.57 mm, SD = 8.74 mm) and mutimodality demons (MAE = 10.07 mm, SD = 4.03 mm). Applying the proposed method on a real MR image sequence also provided qualitatively appealing results, demonstrating good feasibility and applicability of the proposed method. Conclusions: The authors have developed a novel method to estimate the nonrigid motion of GOIs in the presence of spatial intensity and contrast variations, taking advantage of robust shape features. Quantitative analysis and qualitative evaluation demonstrated good promise of the proposed method. Further clinical assessment and validation is being performed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Phase transformations, heat evolution, and atomic diffusion during slow heating of Al-rich Al/Zr multilayered foils

We describe the energy and sequence of phase transformations in multilayered Al/Zr foils with atomic ratios of 3 Al:1 Zr during low temperature (<350 °C) heat treatments in a differential scanning calorimeter. The initial phase formed is an Al-rich amorphous phase that appears to grow by Zr diffusion through the amorphous phase. The subsequent nucleation and growth of tetragonal Al{sub 3}Zr along the Al/amorphous layer interface is mediated by Al diffusion through the crystalline intermetallic phase. Diffusion coefficients associated with these processes are higher than expected from reports of diffusivities measured at higher temperatures. The inferred heat of formation of the tetragonal Al{sub 3}Zr phase is 1240 ± 40 J/g (53 ± 2 kJ/mol atom). No anomalous variation in the energy or sequence of phase transformations is found with bilayer thickness for samples with bilayer thickness in the range of 17 nm to 90 nm despite anomalies in the bilayer dependence of self-propagating reaction velocities in the same foils.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency

Background: Switchgrass, a warm-season perennial grass studied as a potential dedicated biofuel feedstock, is classified into two main taxa – lowland and upland ecotypes – that differ in morphology and habitat of adaptation. But there is limited information on their inherent molecular variations. Results: Transcriptome analysis by RNA-sequencing (RNA-Seq) was conducted for lowland and upland ecotypes to document their gene expression variations. Mapping of transcriptome to the reference genome (Panicum virgatum v1. 1) revealed that the lowland and upland ecotypes differ substantially in sets of genes transcribed as well as levels of expression. Differential gene expression analysis exhibited that transcripts related to photosynthesis efficiency and development and photosystem reaction center subunits were upregulated in lowlands compared to upland genotype. On the other hand, catalase isozymes, helix-loop-helix, late embryogenesis abundant group I, photosulfokinases, and S-adenosyl methionine synthase gene transcripts were upregulated in the upland compared to the lowlands. At ≥100x coverage and ≥5% minor allele frequency, a total of 25,894 and 16,979 single nucleotide polymorphism (SNP) markers were discovered for VS16 (upland ecotype) and K5 (lowland ecotype) against the reference genome. The allele combination of the SNPs revealed that the transition mutations are more prevalent than the transversion mutations. Conclusions: The gene ontology (GO) analysis of the transcriptome indicated lowland ecotype had significantly higher representation for cellular components associated with photosynthesis machinery controlling carbon fixation. In addition, using the transcriptome data, SNP markers were detected, which were distributed throughout the genome. The differentially expressed genes and SNP markers detected in this study would be useful resources for traits mapping and gene transfer across ecotypes in switchgrass breeding for increased biomass yield for biofuel conversion.

09 BIOMASS FUELS↗

Long-period variations in the radial velocity of spectroscopic binary M giant μ Ursae Majoris

We report that the spectroscopic binary μ Ursae Majoris (μ UMa) has secondary RV variations of 471.2 days in addition to those of 230.0 days already known. Keplerian orbit analysis yields stellar mass companions of 1.6 M{sub ⊙} for the 230 day period and 0.14 M{sub ⊙} for the 471 day period. However, the HIPPARCOS photometries show a period similar to the stellar rotational period, which is one-quarter of the RV period. Variations in the bisector velocity curvature show a period of 463.6 days. We also find ∼473 day variations in the equivalent width (EW) measurements of the H{sub α} and H{sub β} lines, whose origin is probably stellar activity. We note that the nature of 471 day variations is similar to one observed in “Sequence D” of Asymptotic Giant Branch pulsating stars. We therefore conclude that the RV and the EW variations in the spectroscopic binary M giant μ UMa A originate from the complex pulsations and the chromospheric activity.

79 ASTRONOMY AND ASTROPHYSICS↗

ROTATIONAL SYNCHRONIZATION MAY ENHANCE HABITABILITY FOR CIRCUMBINARY PLANETS: KEPLER BINARY CASE STUDIES

We report a mechanism capable of reducing (or increasing) stellar activity in binary stars, thereby potentially enhancing (or destroying) circumbinary habitability. In single stars, stellar aggression toward planetary atmospheres causes mass-loss, which is especially detrimental for late-type stars, because habitable zones are very close and activity is long lasting. In binaries, tidal rotational breaking reduces magnetic activity, thus reducing harmful levels of X-ray and ultraviolet (XUV) radiation and stellar mass-loss that are able to erode planetary atmospheres. We study this mechanism for all confirmed circumbinary (p-type) planets. We find that main sequence twins provide minimal flux variation and in some cases improved environments if the stars rotationally synchronize within the first Gyr. Solar-like twins, like Kepler 34 and Kepler 35, provide low habitable zone XUV fluxes and stellar wind pressures. These wide, moist, habitable zones may potentially support multiple habitable planets. Solar-type stars with lower mass companions, like Kepler 47, allow for protected planets over a wide range of secondary masses and binary periods. Kepler 38 and related binaries are marginal cases. Kepler 64 and analogs have dramatically reduced stellar aggression due to synchronization of the primary, but are limited by the short lifetime. Kepler 16 appears to be inhospitable to planets due to extreme XUV flux. These results have important implications for estimates of the number of stellar systems containing habitable planets in the Galaxy and allow for the selection of binaries suitable for follow-up searches for habitable planets.

79 ASTRONOMY AND ASTROPHYSICS↗

Modifying a covarying protein–DNA interaction changes substrate preference of a site-specific endonuclease

Abstract Identifying and validating intermolecular covariation between proteins and their DNA-binding sites can provide insights into mechanisms that regulate selectivity and starting points for engineering new specificity. LAGLIDADG homing endonucleases (meganucleases) can be engineered to bind non-native target sites for gene-editing applications, but not all redesigns successfully reprogram specificity. To gain a global overview of residues that influence meganuclease specificity, we used information theory to identify protein–DNA covariation. Directed evolution experiments of one predicted pair, 227/+3, revealed variants with surprising shifts in I-OnuI substrate preference at the central 4 bases where cleavage occurs. Structural studies showed significant remodeling distant from the covarying position, including restructuring of an inter-hairpin loop, DNA distortions near the scissile phosphates, and new base-specific contacts. Our findings are consistent with a model whereby the functional impacts of covariation can be indirectly propagated to neighboring residues outside of direct contact range, allowing meganucleases to adapt to target site variation and indirectly expand the sequence space accessible for cleavage. We suggest that some engineered meganucleases may have unexpected cleavage profiles that were not rationally incorporated during the design process.

59 BASIC BIOLOGICAL SCIENCES↗

Development of a Protein-based Human Identification Capability from a Single Hair

Shed human hair (lacking root nuclear DNA) frequently contributes important information to forensic investigations involving human identification. Detection of genetic variation observed in amino acid sequences of hair proteins provides a new suite of identity markers that augment microscopic hair analysis and mitochondrial DNA sequencing. In this study, a new method that completely dissolves single hairs using a combination of heat, ultrasonication, and surfactants was developed. Dissolved proteins were digested and genetically variant peptide (GVP) profiles were obtained for single hairs (25 mm) via high–resolution nanoflow liquid chromatography–based mass spectrometry and a novel exome–driven bioinformatic approach. Overall, 6519 unique peptides were identified and a total of 57 GVPs were confirmed. Random match probabilities ranged between 2.6 × 10 –2 and 6.0 × 10 –9 . In conclusion, the new bioinformatic strategy and ability to analyze GVPs in forensically relevant samples sizes demonstrate applicability of this approach to distinguish individuals in forensic contexts.

59 BASIC BIOLOGICAL SCIENCES↗

cis -Regulatory Elements in Plant Development, Adaptation, and Evolution

cis-Regulatory elements encode the genomic blueprints that ensure the proper spatiotemporal patterning of gene expression necessary for appropriate development and responses to the environment. Accumulating evidence implicates changes to gene expression as a major source of phenotypic novelty in eukaryotes, including acute phenotypes such as disease and cancer in mammals. Moreover, genetic and epigenetic variation affecting cis-regulatory sequences over longer evolutionary timescales has become a recurring theme in studies of morphological divergence and local adaptation. Here, we discuss the functions of and methods used to identify various classes of cis-regulatory elements, as well as their role in plant development and response to the environment. We highlight opportunities to exploit cis-regulatory variants underlying plant development and environmental responses for crop improvement efforts. Although a comprehensive understanding of cis-regulatory mechanisms in plants has lagged behind that in animals, we showcase several breakthrough findings that have profoundly influenced plant biology and shaped the overall understanding of transcriptional regulation in eukaryotes.

59 BASIC BIOLOGICAL SCIENCES↗

Cyclic dynamics of misfires and partial burns in a dilute spark-ignition engine

Here, this study investigates the cyclic dynamics of cumulative heat release data past the edge of stability in a dilute spark-ignition engine. Emphasis is placed on analyzing the cyclic dynamics near the dilute limit where partial burns and misfires are frequent. These events are often followed by a higher-energy cycle due to the feed-forward mechanism present in the residual gases. These patterns are deterministic and increase the coefficient of variation to undesirable levels. Symbol sequence analysis was used to investigate the cyclic dynamics of these low–high patterns. The heat release was partitioned on an energy basis to give physical meaning to each partition and each sequence created when analyzing the symbol sequence results. This partitioning method provided insight into the differences in the dynamics when operating in the misfire or partial burn regime. These differences could impact the control method used.

42 ENGINEERING↗

Snails In Silico: A Review of Computational Studies on the Conopeptides

Marine cone snails are carnivorous gastropods that use peptide toxins called conopeptides both as a defense mechanism and as a means to immobilize and kill their prey. These peptide toxins exhibit a large chemical diversity that enables exquisite specificity and potency for target receptor proteins. This diversity arises in terms of variations both in amino acid sequence and length, and in posttranslational modifications, particularly the formation of multiple disulfide linkages. Most of the functionally characterized conopeptides target ion channels of animal nervous systems, which has led to research on their therapeutic applications. Many facets of the underlying molecular mechanisms responsible for the specificity and virulence of conopeptides, however, remain poorly understood. In this review, we will explore the chemical diversity of conopeptides from a computational perspective. First, we discuss current approaches used for classifying conopeptides. Next, we review different computational strategies that have been applied to understanding and predicting their structure and function, from machine learning techniques for predictive classification to docking studies and molecular dynamics simulations for molecular-level understanding. We then review recent novel computational approaches for rapid high-throughput screening and chemical design of conopeptides for particular applications. We close with an assessment of the state of the field, emphasizing important questions for future lines of inquiry.

59 BASIC BIOLOGICAL SCIENCES↗

MTS-VAE

This repository accompanies the work "Design of diverse, functional mitochondrial targeting sequences across eukaryotic organisms using variational autoencoder". It includes the datasets for model training, validation, and downstream analysis.

Mitochondria↗