bluuebunny/crossref_metadata_2025 huggingface dataset:
Applying an interpretable machine learning approach to assess intraspecific trait variation under landscape-scale population differentiation
Authors: Majumder Sambadi , Mason Chase M.
Published: April 2023

Premise

Here we demonstrate the application of interpretable machine learning methods to investigate intraspecific functional trait divergence using diverse genotypes of the wide-ranging sunflowerHelianthus annuusoccupying populations across contrasting ecoregions - the Great Plains versus the North American Deserts.

Methods

Recursive feature elimination was applied to functional trait data from the HeliantHome database, followed by the application of Boruta to detect traits most predictive of ecoregion. Random Forest and Gradient Boosting Machine classifiers were then trained and validated, with results visualized using accumulated local effects plots.

Key Results

The most ecoregion-predictive functional traits span categories of leaf economics, plant architecture, reproductive phenology, and floral and seed morphology. Relative to the Great Plains, genotypes from the North American Deserts exhibit shorter stature, fewer leaves, higher leaf nitrogen, and longer average length of phyllaries.

Conclusions

This approach readily identifies traits predictive of ecoregion origin, and thus functional traits most likely to be responsible for contrasting ecological strategies across the landscape. This type of approach can be used to parse large plant trait datasets in a wide range of contexts, including explicitly testing the applicability of interspecific paradigms at intraspecific scales.
Inhibition of serotonin biosynthesis in neuroendocrine neoplasm suppresses tumor growthin vivo
Authors: Tow Dane H. , Tran Catherine G. , Borbon Luis C. , Ridder Maclain , Li Guiying , Kaemmer Courtney A. , Abusada Ellen , Mahalingam Aswanth Harish , Sadanandam Anguraj , Chandrasekaran Chandrikha , Dillon Joseph , Spitz Douglas R. , Quelle Dawn E. , Chan Carlos H.F. , Bellizzi Andrew , Howe James R. , Ear Po Hien
Published: April 2023

Small bowel neuroendocrine tumors (SBNETs) originate from enterochromaffin cells in the intestine which synthesize and secrete serotonin. SBNETs express high levels of tryptophan hydroxylase 1 (Tph1), a key enzyme in serotonin biosynthesis. Patients with high serotonin level may develop carcinoid syndrome, which can be treated with somatostatin analogues and the Tph1 inhibitor telotristat ethyl in severe cases. Although the active drug telotristat can efficiently reduce serotonin levels, its effect on tumor growth is unclear. This study determined the effect of serotonin inhibition on tumor cell growthin vitroandin vivo. The levels of Tph1 in various neuroendocrine neoplasms (NENs) were determined and the biological effects of Tph1 inhibitionin vitroandin vivousing genetic and pharmacologic approaches was tested. Gene and protein expression analyses were performed on patient tumors and cancer cell lines. shRNAs targetingTPH1were used to create stable knockdown in BON cells. Control and knockdown lines were assessed for their growth ratesin vitroandin vivo, angiogenesis potential, serotonin levels, endothelial cell tube formation, tumor weight, and tumor vascularity.TPH1is highly expressed in SBNETs and many cancer types.TPH1knockdown cells and telotristat treated cells showed similar growth rates as control cellsin vitro. However,TPH1knockdown cells formed smaller tumorsin vivoand tumors were less vascularized. Although Tph1 inhibition with telotristat showed no effect on tumor cell growthin vitro, Tph1 inhibition reduced tumor formationin vivo. Serotonin inhibition in combination with other therapies is a promising new avenue for targeting metabolic vulnerabilities in NENs.
Prediction of virus-host associations using protein language models and multiple instance learning
Authors: Liu Dan , Young Francesca , Robertson David L , Yuan Ke
Published: April 2023

Predicting virus-host associations is essential to determine the specific host species that viruses interact with, and discover if new viruses infect humans and animals. Currently, the host of the majority of viruses is unknown, particularly in microbiomes. To address this challenge, we introduce EvoMIL, a deep learning method that predicts the host species for viruses from viral sequences only. It also identifies important viral proteins that significantly contribute to host prediction. The method combines a pre-trained large protein language model (ESM) and attention-based multiple instance learning to allow protein-orientated predictions. Our results show that protein embeddings capture stronger predictive signals than sequence composition features, including amino acids, physiochemical properties, and DNA k-mers. In multi-host prediction tasks, EvoMIL achieves median F1 score improvements of 8.6%, 12.3%, and 4.1% in prokaryotic hosts, and 0.5%, 1.8% and 3% in eukaryotic hosts. EvoMIL binary classifiers achieve impressive AUC over 0.95 for all prokaryotic and range from roughly 0.8 to 0.9 for eukaryotic hosts. Furthermore, EvoMIL estimates the importance of single proteins in the prediction task and maps them to an embedding landscape of all viral proteins, where proteins with similar functions are distinctly clustered together, highlighting the ability of EvoMIL to capture key proteins in virus-host specificity.

Author summary

Being able to predict which viruses can infect which host species, and identifying the specific proteins that are involved in these interactions, are fundamental tasks in virology. Traditional methods for predicting these interactions rely on common manual features among proteins, overlooking the structure of the protein ”language” encoded in individual proteins. We have developed a novel method that combines a protein language model and multiple instance learning to allow host prediction directly from protein sequences, without the need to extract manual features. This method significantly improved prediction accuracy and revealed key proteins involved in virus-host interactions.
The Chromatin Landscape of Pathogenic Transcriptional Cell States in Rheumatoid Arthritis
Authors: Weinand Kathryn , Sakaue Saori , Nathan Aparna , Jonsson Anna Helena , Zhang Fan , Watts Gerald F. M. , Zhu Zhu ,   Accelerating Medicines Partnership Program: 5 Rheumatoid Arthritis and Systemic Lupus Erythematosus (AMP RA/SLE) Network, Rao Deepak A. , Anolik Jennifer H. , Brenner Michael B. , Donlin Laura T. , Wei Kevin , Raychaudhuri Soumya
Published: April 2023

Synovial tissue inflammation is the hallmark of rheumatoid arthritis (RA). Recent work has identified prominent pathogenic cell states in inflamed RA synovial tissue, such as T peripheral helper cells; however, the epigenetic regulation of these states has yet to be defined. We measured genome-wide open chromatin at single cell resolution from 30 synovial tissue samples, including 12 samples with transcriptional data in multimodal experiments. We identified 24 chromatin classes and predicted their associated transcription factors, including aCD8+GZMK+ class associated with EOMES and a lining fibroblast class associated with AP-1. By integrating an RA tissue transcriptional atlas, we found that the chromatin classes represented ‘superstates’ corresponding to multiple transcriptional cell states. Finally, we demonstrated the utility of this RA tissue chromatin atlas through the associations between disease phenotypes and chromatin class abundance as well as the nomination of classes mediating the effects of putatively causal RA genetic variants.
Pan-cancer analysis of the ion permeome reveals functional regulators of glioblastoma aggression
Authors: Bahcheli Alexander T. , Min Hyun-Kee , Bayati Masroor , Dong Weifan , Fortuna Alexander , Zhao Hongyu , Dzneladze Irakli , Chan Jade , Chen Xin , Guevara-Hoyer Kissy , Dirks Peter B. , Huang Xi , Reimand Jüri
Published: April 2023

Ion channels, transporters, and other ion-permeating proteins, collectively comprising the ion permeome (IP), are common drug targets. However, their roles in cancer are understudied. Our integrative pan-cancer analysis shows that IP genes display highly-elevated expression patterns in subsets of cancer samples significantly more often than expected transcriptome-wide. To enable target identification, we identified 410 survival-associated IP genes in 29 cancer types using a machine learning approach. Notably,GJB2andSCN9Ashow prominent expression in neoplastic cells and associate with poor prognosis in glioblastoma (GBM), the most common and aggressive brain cancer.GJB2orSCN9Aknockdown in patient-derived GBM cells induces transcriptome-wide changes involving neural projection and proliferation pathways, impairs cell viability and tumor sphere formation, mitigates tunneling nanotube formation, and extends the survival of GBM-bearing mice. Thus, aberrant activation of IP genes appears as a pan-cancer feature of tumor heterogeneity that can be exploited for mechanistic insights and therapy development.
The Rous sarcoma virus Gag polyprotein forms biomolecular condensates driven by intrinsically-disordered regions
Authors: Maldonado Rebecca Kaddis , Rice Breanna L. , Lambert Gregory S. , Sudol Malgorzata , Flanagan John M. , Parent Leslie J.
Published: April 2023

Biomolecular condensates (BMCs) play important roles in cellular structures including transcription factories, splicing speckles, and nucleoli. BMCs bring together proteins and other macromolecules, selectively concentrating them so that specific reactions can occur without interference from the surrounding environment. BMCs are often made up of proteins that contain intrinsically disordered regions (IDRs), form phase-separated spherical puncta, form liquid-like droplets that undergo fusion and fission, contain molecules that are mobile, and are disrupted with phase-dissolving drugs such as 1,6-hexanediol. In addition to cellular proteins, many viruses, including influenza A, SARS-CoV-2, and human immunodeficiency virus type 1 (HIV-1) encode proteins that undergo phase separation and rely on BMC formation for replication. In prior studies of the retrovirus Rous sarcoma virus (RSV), we observed that the Gag protein forms discrete spherical puncta in the nucleus, cytoplasm, and at the plasma membrane that co-localize with viral RNA and host factors, raising the possibility that RSV Gag forms BMCs that participate in the virion intracellular assembly pathway. In our current studies, we found that Gag contains IDRs in the N-terminal (MAp2p10) and C-terminal (NC) regions of the protein and fulfills many criteria of BMCs. Although the role of BMC formation in RSV assembly requires further study, our results suggest the biophysical properties of condensates are required for the formation of Gag complexes in the nucleus and the cohesion of these complexes as they traffic through the nuclear pore, into the cytoplasm, and to the plasma membrane, where the final assembly and release of virus particles occurs.
Perceptual Transitions between Object Rigidity & Non-rigidity: Competition and cooperation between motion-energy, feature-tracking and shape-based priors
Authors: Maruya Akihito , Zaidi Qasim
Published: April 2023

Why do moving objects appear rigid when projected retinal images are deformed non-rigidly? We used rotating rigid objects that can appear rigid or non-rigid to test whether shape features contribute to rigidity perception. When two circular rings were rigidly linked at an angle and jointly rotated at moderate speeds, observers reported that the rings wobbled and were not linked rigidly but rigid rotation was reported at slow speeds. When gaps, paint or vertices were added, the rings appeared rigidly rotating even at moderate speeds. At high speeds, all configurations appeared non-rigid. Salient features thus contribute to rigidity at slow and moderate speeds, but not at high speeds. Simulated responses of arrays of motion-energy cells showed that motion flow vectors are predominantly orthogonal to the contours of the rings, not parallel to the rotation direction. A convolutional neural network trained to distinguish flow patterns for wobbling versus rotation, gave a high probability of wobbling for the motion-energy flows. However, the CNN gave high probabilities of rotation for motion flows generated by tracking features with arrays of MT pattern-motion cells and corner detectors. In addition, circular rings can appear to spin and roll despite the absence of any sensory evidence, and this illusion is prevented by vertices, gaps, and painted segments, showing the effects of rotational symmetry and shape. Combining CNN outputs that give greater weight to motion energy at fast speeds and to feature tracking at slow, with the shape-based priors for wobbling and rolling, explained rigid and nonrigid percepts across shapes and speeds (R2=0.95). The results demonstrate how cooperation and competition between different neuronal classes leads to specific states of visual perception and to transitions between the states.
Biofabrication of nanocomposite-based scaffolds containing human bone extracellular matrix for the differentiation of skeletal stem and progenitor cells
Authors: Kim Yang-Hee , Kanczler Janos M , Lanham Stuart , Rawlings Andrew , Roldo Marta , Tozzi Gianluca , Dawson Jonathan I. , Cidonio Gianluca , Oreffo Richard O.C
Published: April 2023

Autograft or metal implants are routinely used in skeletal repair but can fail to provide a long-term clinical resolution, emphasising the need for a functional biomimetic tissue engineering alternative. An attractive sustainable opportunity for tissue regeneration would be the application of human bone waste tissue for the synthesis of a material ink for 3D bioprinting of skeletal tissue.

The use of human bone extracellular matrix (bone-ECM) offers an exciting potential for the development of an appropriate micro-environment for human bone marrow stromal cells (HBMSCs) to proliferate and differentiate along the osteogenic lineage. Extrusion-based deposition was mediated by the blending of human bone-ECM (B) with nanoclay (L, Laponite®) and alginate (A) polymer, to engineer a novel material ink (LAB). The inclusion of nanofiller and polymeric material increased the rheological, printability, and drug retention properties and, critically, the preservation of HBMSCs viability upon printing. The composite human bone-ECM-based 3D constructs containing vascular endothelial growth factor (VEGF) enhanced vascularisation following implantation in anex vivochick chorioallantoic membrane (CAM) model. Addition of bone morphogenetic protein-2 (BMP-2) with HBMSCs further enhanced vascularisation together with mineralisation after only 7 days.

The current study demonstrates the synergistic combination of nanoclay with biomimetic materials, (alginate and bone-ECM) to support the formation of osteogenic tissue bothin vitroandex vivoand offers a promising novel 3D bioprinting approach to personalised skeletal tissue repair.

Graphical Abstract

Engineering nanoclay-based bone ECM novel bioink for bone regeneration. Human bone trabecular tissue was demineralised, decellularised and blended with nanoclay (Laponite®) and alginate after digestion. The resulting ink was investigated for printability following rheological and filament fusion investigation. The microstructural arrangement of the blends was examined together with viability and functionality of bioprinted HBMSCs. Finally, the ability of the novel blend to support drug release ex vivo in a CAM model was determined confirming the potential of the bone ECM ink to support bone formation.
A statistical framework for quantifying the nuclear export rate of influenza viral mRNAs
Authors: Miura Michi , Kiuchi Naho , Lau Siu-Ying , Mok Bobo Wing-Yee , Ushirogawa Hiroshi , Naito Tadasuke , Chen Honglin , Saito Mineki
Published: April 2023

Influenza A virus transcribes viral mRNAs from the eight segmented viral genome when it infects. The kinetics of viral transcription, nuclear export of viral transcripts, and their potential variation between the eight segments are poorly characterised. Here we introduce a statistical framework for estimating the nuclear export rate of each segment from a snapshot ofin situmRNA localisation. This exploits the cell-to-cell variation at a single time point observed by an imaging-basedin situtranscriptome assay. Using our model, we revealed the variation in the mRNA nuclear export rate of the eight viral segments. Notably, the two influenza viral antigens hemagglutinin and neuraminidase were the slowest segments in the nuclear export, suggesting the possibility that influenza A virus uses the nuclear retention of viral transcripts to delay the expression of antigenic molecules. Our framework presented in this study can be widely used for investigating the nuclear retention of nascent transcripts produced in a transcription burst.
Independently evolved pollution resistance in four killifish populations is largely explained by few variants of large effect
Authors: Miller Jeffrey T. , Clark Bryan W. , Reid Noah M. , Karchner Sibel I. , Roach Jennifer L. , Hahn Mark E. , Nacci Diane , Whitehead Andrew
Published: April 2023

The genetic architecture of phenotypic traits can affect the mode and tempo of trait evolution. Human-altered environments can impose strong natural selection, where successful evolutionary adaptation requires swift and large phenotypic shifts. In these scenarios, theory predicts the influence of few adaptive variants of large effect, but empirical studies that have revealed the genetic architecture of rapidly evolved phenotypes are rare, especially for populations inhabiting polluted environments.Funduluskillifish have repeatedly evolved adaptive resistance to extreme pollution in urban estuaries. Prior studies, including genome scans for signatures of natural selection, have revealed some of the genes and pathways important for evolved pollution resistance, and provide context for the genotype-phenotype association studies reported here. We created multiple quantitative trait locus (QTL) mapping families using progenitors from four different resistant populations, and genetically mapped variation in sensitivity (developmental perturbations) following embryonic exposure to a model toxicant PCB-126. We found that a few large-effect QTL loci accounted for resistance to PCB- mediated developmental toxicity. QTLs harbored candidate genes that govern the regulation of aryl hydrocarbon receptor (AHR) signaling, where some (but not all) of these QTL loci were shared across all populations, and some (but not all) of these loci showed signatures of recent natural selection in the corresponding wild population. Some strong candidate genes for PCB resistance inferred from genome scans in wild populations were identified as QTL, but some key candidate genes were not. We conclude that rapidly evolved resistance to the developmental defects normally caused by PCB-126 is governed by few genes of large effect. However, other aspects of resistance beyond developmental phenotypes may be governed by additional loci, such that comprehensive resistance to PCB-126, and to the mixtures of chemicals that distinguish urban estuaries more broadly, may be more genetically complex.
SynDISCO: A Mechanistic Modeling-Based Framework for Predictive Prioritization of Synergistic Drug Combinations Directed at Cell Signaling Networks
Authors: Shin Sung-Young , Nguyen Lan K.
Published: April 2023

The widespread development of resistance to cancer monotherapies has prompted the need to identify combinatorial treatment approaches that circumvent drug resistance and achieve more durable clinical benefit. However, given the vast space of possible combinations of existing drugs, the inaccessibility of drug screens to candidate targets with no available drugs, and the significant heterogeneity of cancers, exhaustive experimental testing of combination treatments remains highly impractical. There is thus an urgent need to develop computational approaches that complement experimental efforts and aid the identification and prioritization of effective drug combinations. Here, we provide a practical guide to SynDISCO, a computational framework that leverages mechanistic ODE modeling to predict and prioritize synergistic combination treatments directed at signaling networks. We demonstrate the key steps of SynDISCO and its application to the EGFR-MET signaling network in triple negative breast cancer as an illustrative example. SynDISCO is, however, a network- and cancer-independent framework, and given a suitable ODE model of the network of interest, it could be leveraged to discover cancer-specific combination treatments.
Experimental validation of computational models for the prediction of phase distribution during multi-channel transcranial alternating current stimulation
Authors: Lee Sangjun , Shirinpour Sina , Alekseichuk Ivan , Perera Nipun , Linn Gary , Schroeder Charles E. , Falchier Arnaud Y. , Opitz Alexander
Published: April 2023

Transcranial alternating current stimulation (tACS) is a widely used noninvasive brain stimulation (NIBS) technique to affect neural activity. Neural oscillations exhibit phase-dependent associations with cognitive functions, and tools to manipulate local oscillatory phases can affect communication across remote brain regions. A recent study demonstrated that multi-channel tACS can generate electric fields with a phase gradient or traveling waves in the brain. Computational simulations using phasor algebra can predict the phase distribution inside the brain and aid in informing parameters in tACS experiments. However, experimental validation of computational models for multi-phase tACS is still lacking. Here, we develop such a framework for phasor simulation and evaluate its accuracy usingin vivorecordings in nonhuman primates. We extract the phase and amplitude of electric fields from intracranial recordings in two monkeys during multi-channel tACS and compare them to those calculated by phasor analysis using finite element models. Our findings demonstrate that simulated phases correspond well to measured phases (r = 0.9). Further, we systematically evaluated the impact of accurate electrode placement on modeling and data agreement. Finally, our framework can predict the amplitude distribution in measurements given calibrated tissues’ conductivity. Our validated general framework for simulating multi-phase, multi-electrode tACS provides a streamlined tool for principled planning of multi-channel tACS experiments.
Tree-based QTL mapping with expected local genetic relatedness matrices
Authors: Link Vivian , Schraiber Joshua G. , Fan Caoqi , Dinh Bryan , Mancuso Nicholas , Chiang Charleston W.K. , Edge Michael D.
Published: April 2023

Understanding the genetic basis of complex phenotypes is a central pursuit of genetics. Genome-wide Association Studies (GWAS) are a powerful way to find genetic loci associated with phenotypes. GWAS are widely and successfully used, but they face challenges related to the fact that variants are tested for association with a phenotype independently, whereas in reality variants at different sites are correlated because of their shared evolutionary history. One way to model this shared history is through the ancestral recombination graph (ARG), which encodes a series of local coalescent trees. Recent computational and methodological breakthroughs have made it feasible to estimate approximate ARGs from large-scale samples. Here, we explore the potential of an ARG-based approach to quantitative-trait locus (QTL) mapping, echoing existing variance-components approaches. We propose a framework that relies on the conditional expectation of a local genetic relatedness matrix given the ARG (local eGRM). Simulations show that our method is especially beneficial for finding QTLs in the presence of allelic heterogeneity. By framing QTL mapping in terms of the estimated ARG, we can also facilitate the detection of QTLs in understudied populations. We use local eGRM to identify a large-effect BMI locus, theCREBRFgene, in a sample of Native Hawaiians in which it was not previously detectable by GWAS because of a lack of population-specific imputation resources. Our investigations can provide intuition about the benefits of using estimated ARGs in population- and statistical-genetic methods in general.
An Ecological Study on the Associations of County-Based Credit Ratings with Age-Adjusted Mortality Rates in Michigan
Authors: Rogers John P , Dempsey Tyler J
Published: April 2023

The objective of this study was to examine the association and implications between 21 Michigan county-specific credit ratings and age-adjusted mortality rates averaged across six quarters of county-specific data. Pearson’s regression analysis was performed and indicated that county credit ratings were significantly associated with average age-adjusted county mortality rates (r = 0.7715, p = 0.0000421), with lower county credit ratings corresponding to higher average age-adjusted county mortality rates. The results indicate that county credit ratings are associated with negative public health outcomes specific to that county, which the investigators propose mechanistically relates difficulty of local governments ascertaining low-cost funding for community health, infrastructure, and economic development projects.
Neural encoding of multiple motion speeds in visual cortical area MT
Authors: Huang Xin , Ghimire Bikalpa , Chakrala Anjani Sreeprada , Wiesner Steven
Published: April 2023

Segmenting objects from each other and their background is critical for vision. The speed at which objects move provides a salient cue for segmentation. However, how the visual system represents and differentiates multiple speeds is largely unknown. Here we investigated the neural encoding of multiple speeds of overlapping stimuli in the primate visual cortex. We first characterized the perceptual capacity of human and monkey subjects to segment spatially overlapping stimuli moving at different speeds. We then determined how neurons in the motion-sensitive, middle-temporal (MT) cortex of macaque monkeys encode multiple speeds. We made a novel finding that the responses of MT neurons to two speeds of overlapping stimuli showed a robust bias toward the faster speed component when both speeds were slow (≤ 20°/s). The faster-speed bias occurred even when a neuron had a slow preferred speed and responded more strongly to the slower component than the faster component when presented alone. The faster-speed bias emerged very early in neuronal response and was robust over time and to manipulations of motion direction and attention. As the stimulus speed increased, the faster-speed bias changed to response averaging. Our finding can be explained by a modified divisive normalization model, in which the weights for the speed components are proportional to the responses of a population of neurons elicited by the individual speeds. Our results suggest that the neuron population, referred to as the weighting pool, includes neurons that have a broad range of speed preferences. As a result, the response weights for the speed components are determined by the stimulus speeds and invariant to the speed preferences of individual neurons. Our findings help to define the neural encoding rule of multiple stimuli and provide new insight into the underlying neural mechanisms. The faster-speed bias would benefit behavioral tasks such as figure-ground segregation if figural objects tend to move faster than the background in the natural environment.
Latent taste diversity revealed by a vertebrate-wide catalogue of T1R receptors
Authors: Nishihara Hidenori , Toda Yasuka , Kuramoto Tae , Kamohara Kota , Goto Azusa , Hoshino Kyoko , Okada Shinji , Kuraku Shigehiro , Okabe Masataka , Ishimaru Yoshiro
Published: April 2023

Taste is a vital chemical sense for feeding behavior. In mammals, the umami and sweet taste receptors are composed of three members of the taste receptor type 1 (T1R/TAS1R) family: T1R1, T1R2, and T1R3. Because their functional homologs exist in teleosts, only threeTAS1Rgenes generated by gene duplication are believed to have been inherited from the common ancestor of bony vertebrates. Here, we report five previously uncharacterizedTAS1Rmembers in vertebrates, namedTAS1R4,5,6,7, andTAS1Rcf, through a genome-wide survey of diverse taxa. ForTAS1R2andTAS1R3, mammalian and teleost fish genes were found to be paralogous. Phylogenetic analysis suggests that the bony vertebrate ancestor had nineTAS1Rsdue to multiple gene duplications, and someTAS1Rs were lost independently in each lineage; ultimately, mammals and teleosts have retained only threeTAS1Rs, whereas other lineages have retained moreTAS1Rs. Functional assays and expression analysis in non-teleost fishes suggest that the novel T1Rs form heterodimers in taste receptor cells and contribute to the recognition of a broad range of ligands such as essential amino acids, including branched-chain amino acids, which were not previously considered as T1R ligands. These results highlight an unexpected diversity of taste sensations in both modern and the ancestors of vertebrates. The complex evolution of the taste receptor family might have enabled vertebrates to adapt to diverse habitats on Earth.
Measuring human cerebral blood flow and brain function with fiber-based speckle contrast optical spectroscopy system
Authors: Kim Byungchan , Zilpelwar Sharvari , Sie Edbert J. , Marsili Francesco , Zimmermann Bernhard , Boas David A. , Cheng Xiaojun
Published: April 2023

Cerebral blood flow (CBF) is an important indicator of brain health and function. Diffuse correlation spectroscopy (DCS) is an optical technique that enables non-invasive and continuous bedside monitoring of human CBF. However, traditional DCS consisting of a few channels has relatively low signal-to-noise ratio (SNR), preventing measurements at long source detector separations (SDS) with increased sensitivity to cerebral rather than extracerebral blood flow. Here we developed a fiber-based speckle contrast optical spectroscopy (SCOS) system and the corresponding data analysis pipeline to measure CBF variations. We show that SCOS outperforms traditional DCS by more than an order of magnitude in SNR with comparable financial cost. We also demonstrated human brain function measurements during a cognitive task at an SDS of 33mm. This technology will establish the foundation for devices that use spatial speckle statistics to non-invasively monitor human CBF, leading to a new functional neuroimaging approach for cognitive neuroscience.
piTracer - Automatic reconstruction of molecular cascades for the identification of synergistic drug targets
Authors: Gomari Daniel , Achkar Iman W. , Benedetti Elisa , Tabling Jan , Halama Anna , Krumsiek Jan
Published: April 2023

Cancer cells frequently undergo metabolic reprogramming as a mechanism of resistance against chemotherapeutic drugs. Metabolomic profiling provides a direct readout of metabolic changes and can thus be used to identify these tumor escape mechanisms. Here, we introduce piTracer, a computational tool that uses multi-scale molecular networks to identify potential combination therapies from pre- and post-treatment metabolomics data. We first demonstrate piTracer’s core ability to reconstruct cellular cascades by inspecting well-characterized molecular pathways and previously studied associations between genetic variants and metabolite levels. We then apply a new gene ranking algorithm on differential metabolomic profiles from human breast cancer cells after glutaminase inhibition. Four of the automatically identified gene targets were experimentally tested by simultaneous inhibition of the respective targets and glutaminase. Of these combination treatments, two were be confirmed to induce synthetic lethality in the cell line. In summary, piTracer integrates the molecular monitoring of escape mechanisms into comprehensive pathway networks to accelerate drug target identification. The tool is open source and can be accessed athttps://github.com/krumsieklab/pitracer.
Cell cycle regulation of the psoriasis associated geneCCHCR1by transcription factor E2F1
Authors: Ling Yick Hin , Chen Yingying , Leung Kwok Nam , Chan King Ming , Liu Wing Keung
Published: April 2023

The coiled-coil alpha-helical rod protein 1 (CCHCR1) was first identified as a candidate gene in psoriasis and has lately been associated with COVID-19 susceptibility. Located within P-bodies and centrosomes, its exact cellular role and transcriptional control remain largely unknown. Here, we showed thatCCHCR1shares a bidirectional promoter with its neighboring gene,TCF19. This bidirectional promoter is activated by the G1/S-regulatory transcription factor E2F1, and both genes are co-induced during the G1/S transition of the cell cycle. A luciferase reporter assay suggests that the short intergenic sequence, only 287 bp in length, is sufficient for the G1/S induction of both genes, but the expression ofCCHCR1is further enhanced by the presence of exon 1 from bothTCF19andCCHCR1. This research uncovers the transcriptional regulation of theCCHCR1gene, offering new perspectives on its function. These findings contribute to the broader understanding of diseases associated with CCHCR1 and may serve as a foundational step for future research in these vital medical fields.
C. elegansmales optimize mate-choice decisions via sex-specific responses to multimodal sensory cues
Authors: Luo Jintao , Barrios Arantza , Portman Douglas S.
Published: April 2023

For sexually reproducing animals, selecting optimal mates is essential for maximizing reproductive fitness. Because the nematodeC. elegansreproduces mostly by self-fertilization, little is known about its mate-choice behaviors. While several sensory cues have been implicated in males’ ability to recognize hermaphrodites, achieving an integrated understanding of the ways males use these cues to assess relevant characteristics of potential mates has proven challenging. Here, we use a choice-based social-interaction assay to explore the ability ofC. elegansmales to make and optimize mate choices. We find that males use a combination of volatile sex pheromones (VSPs), ascaroside pheromones, surface-bound chemical cues, and other signals to robustly assess a variety of features of potential mates. Specific aspects of mate choice are communicated by distinct signals: the presence of a sperm-depleted, receptive hermaphrodite is likely signaled by VSPs, while developmental stage and sex are redundantly specified by ascaroside pheromones and surface-associated cues. Ascarosides also signal nutritional information, allowing males to choose well-fed over starved mates, while both ascarosides and surface-associated cues cause males to prefer virgin over previously mated hermaphrodites. The male-specificity of these behavioral responses is determined by both male-specific neurons and the male state of sex-shared circuits, and we reveal an unexpected role for the sex-shared ASH sensory neurons in male attraction to endogenously produced hermaphrodite ascarosides. Together, our findings lead to an integrated view of the signaling and behavioral mechanisms by which males use diverse sensory cues to assess multiple features of potential mates and optimize mate choice.
The Influence of Angiotensin II on the Gut Microbiome of Mice: Findings from a Retrospective Study
Authors: Muralitharan Rikeish R. , Nakai Michael E. , Snelson Matthew , Zheng Tenghao , Dinakis Evany , Xie Liang , Jama Hamdi , Paterson Madeleine , Shihata Waled , Wassef Flavia , Vinh Antony , Drummond Grant R. , Kaye David M. , Mackay Charles R. , Marques Francine Z.
Published: April 2023

Introduction

Animal models are regularly used to test the role of the gut microbiome in hypertension. Small-scale pre-clinical studies have investigated changes to the gut microbiome in the angiotensin II hypertensive model. However, the gut microbiome is influenced by internal and external factors not regularly considered in the study design. Once these factors are accounted for, it is unclear if microbiome signatures are reproduceable. We aimed to determine the influence of angiotensin II treatment on the gut microbiome using a large and diverse cohort of mice and to quantify the magnitude by which other factors contribute to microbiome variations.

Methods and Results

We conducted a retrospective study to establish a diverse mouse cohort resembling large human studies. We sequenced the V4 region of the 16S rRNA gene from 538 samples across the gastrointestinal tract of 303 male and female C57BL/6J mice randomised into sham or angiotensin II treatment from different genotypes, diets, animal facilities, and age groups. Analysing over 17 million sequencing reads, we observed that angiotensin II treatment influenced α-diversity (P=0.0137) and β-diversity (i.e., composition of the microbiome, P<0.001). Bacterial abundance analysis revealed patterns consistent with a reduction in short-chain fatty acid-producers, microbial metabolites that lower blood pressure. Furthermore, animal facility, genotype, diet, age, sex, intestinal sampling site, and sequencing batch had significant effects on both α- and β-diversity (all P<0.001). Sampling site (6.8%) and diet (6%) had the largest impact on the microbiome, while angiotensin II and sex had the smallest effect (each 0.4%).

Conclusions

Our large-scale data confirmed findings from small-scale studies that angiotensin II impacted the gut microbiome. However, this effect was modest relative to most of the other factors studied. Accounting for these factors in future pre-clinical hypertensive studies will increase the likelihood that microbiome findings are replicable and translatable.
Senescence triggers intracellular acidification and lysosomal alkalinization via ATP6AP2 attenuation in breast cancer cells
Authors: Li Wei , Kawaguchi Kosuke , Tanaka Sunao , He Chenfeng , Maeshima Yurina , Suzuki Eiji , Toi Masakazu
Published: April 2023

Several chemotherapy drugs induce the senescence of cancer cells; however, the mechanism underlying intracellular pH dysregulation in senescent cells remains unclear. Adenosine triphosphatase H+ transporting accessory protein 2 (ATP6AP2) plays a critical role in maintaining pH homeostasis in cellular compartments. We here report a new function of ATP6AP2 in senescent breast cancer cells induced by doxorubicin and abemaciclib treatment. ATP6AP2 expression was significantly downregulated in senescent cells, leading to aberrant pH levels that impaired lysosome function and caused immune response changes. The drugs caused cell cycle arrest and proliferation suppression through the upregulation of senescence-related genes. Additionally, senescent cells showed altered inflammatory and immune transcriptional profiles by reprogramming the senescence-associated secretory phenotype. These findings suggest that ATP6AP2-mediated pH regulation during therapy-induced senescence may be linked to immune changes in senescent cancer cells. These findings provide novel insights into understanding the cellular mechanisms underlying the response to anti-cancer drugs.
Phyloecology ofnrfA-ammonifiers and their relative importance with denitrifiers in global terrestrial biomes
Authors: Saghaï Aurélien , Pold Grace , Jones Christopher M. , Hallin Sara
Published: April 2023

Nitrate ammonification is important for soil nitrogen retention. However, the ecology of nitrate ammonifiers and their prevalence compared with denitrifiers, being competitors for nitrate, are overlooked. Here, we screened more than 1 million genomes fornrfA, encoding the nitrite reductase in nitrate ammonification. Nearly 50% of the nitrate ammonifier assemblies carry at least one denitrification gene and, contrary to the current paradigm, have higher potential for nitrous oxide production than reduction. We then used a phylogeny-based approach to recruitnrfAand denitrification nitrite reductase gene fragments in 1,861 metagenomes covering the major terrestrial biomes. Denitrification genes dominated, except in tundra, and random forest modelling teased apart the influence of the soil C/N on nitrate ammonifier vs denitrifier abundances, showing an effect of nitrate rather than carbon content. This study demonstrates the multiple roles nitrate ammonifiers play in nitrogen cycling and the factors ultimately controlling the fate of nitrate in soil.
A model for co-occurrent assortative mating and vertical cultural transmission and its impact on measures of genetic associations
Authors: Herzig Anthony F. , Noûs Camille , Pierre Aude Saint , Perdry Hervé
Published: April 2023

Assortative mating for a given phenotype is the phenomenon by which mates select each other based on their phenotypic similarity. Other phenomena can create positive correlation between the parents’ and the offspring’s environment: vertical cultural transmission, or dynastic effects. When these phenomena occur together, they induce a gene-environment correlation at the population scale. It will impact genetic measures of associations such as SNP effect size and SNP-heritability.

In this paper, we provide a complete mathematical modeling of this phenomenon, in the classical framework of the polygenic additive model. We then derive its consequences on typical genetic epidemiology study designs. We validate our calculations through simple forward-time simulations.
Decoupling of evolutionary changes in mRNA and protein levels
Authors: Jiang Daohan , Cope Alexander L. , Zhang Jianzhi , Pennell Matt
Published: April 2023

Variation in gene expression across lineages is thought to explain much of the observed phenotypic variation and adaptation. The protein is closer to the target of natural selection but gene expression is typically measured as the amount of mRNA. The broad assumption that mRNA levels are good proxies for protein levels has been undermined by a number of studies reporting moderate or weak correlations between the two measures across species. One biological explanation for this discrepancy is that there has been compensatory evolution between the mRNA level and regulation of translation. However, we do not understand the evolutionary conditions necessary for this to occur nor the expected strength of the correlation between mRNA and protein levels. Here we develop a theoretical model for the coevolution of mRNA and protein levels and investigate the dynamics of the model over time. We find that compensatory evolution is widespread when there is stabilizing selection on the protein level, which is true across a variety of regulatory pathways. When the protein level is under directional selection, the mRNA level of a gene and its translation rate of the same gene were negatively correlated across lineages but positively correlated across genes. These findings help explain results from comparative studies of gene expression and potentially enable researchers to disentangle biological and statistical hypotheses for the mismatch between transcriptomic and proteomic studies.
Bacterial mixed cultures followed mixed-order kinetics during mono-azo dye decolourization and degradation in batch studies
Authors: Jain Kunal R. , Chapla Digantkumar , Shah Amita , Madamwar Datta
Published: April 2023

Over the years little has been focused on kinetic and thermodynamic aspect of bioremediation studies on dyes. In this study, detailed kinetic and thermodynamic analyses of results obtained during a primary study on a mono-azo dye: Reactive violet 5R (RV5), decolourization and degradation by bacterial mixed cultures SB4 were performed. Various kinetic models (zero-, first- and second-order behaviour and Monod model) were applied to understand the decolourization mechanism in batch process. Similarly, steady-state kinetics for determination of Michaelis-constant and maximal dye removal rate was derived. With increasing RV5 concentration, the specific decolourization rate had increased from 0.61mg/L/h to 1.38mg/L/h. The apparent kinetics of RV5 decolourization reaction followed mixed-order behaviour. The process was endothermic. The enthalpy and entropy values calculated to 45.6kJ/mol and 146J/mol/K, respectively, with an activation energy of 87kJ/mol. The Gibbs free energy change suggests that, decolourization reaction under experimental conditions was non-spontaneous below 20°C but was spontaneous at higher temperatures.
Comparative single cell epigenomic analysis of gene regulatory programs in the rodent and primate neocortex
Authors: Zemke Nathan R , Armand Ethan J , Wang Wenliang , Lee Seoyeon , Zhou Jingtian , Li Yang Eric , Liu Hanqing , Tian Wei , Nery Joseph R. , Castanon Rosa G , Bartlett Anna , Osteen Julia K , Li Daofeng , Zhuo Xiaoyu , Xu Vincent , Miller Michael , Krienen Fenna M. , Zhang Qiangge , Taskin Naz , Ting Jonathan , Feng Guoping , McCarroll Steven A , Callaway Edward M , Wang Ting , Behrens M Margarita , Lein Ed S , Ecker Joseph R , Ren Bing
Published: April 2023

Sequence divergence ofcis-regulatory elements drives species-specific traits, but how this manifests in the evolution of the neocortex at the molecular and cellular level remains to be elucidated. We investigated the gene regulatory programs in the primary motor cortex of human, macaque, marmoset, and mouse with single-cell multiomics assays, generating gene expression, chromatin accessibility, DNA methylome, and chromosomal conformation profiles from a total of over 180,000 cells. For each modality, we determined species-specific, divergent, and conserved gene expression and epigenetic features at multiple levels. We find that cell type-specific gene expression evolves more rapidly than broadly expressed genes and that epigenetic status at distal candidatecis-regulatory elements (cCREs) evolves faster than promoters. Strikingly, transposable elements (TEs) contribute to nearly 80% of the human-specific cCREs in cortical cells. Through machine learning, we develop sequence-based predictors of cCREs in different species and demonstrate that the genomic regulatory syntax is highly preserved from rodents to primates. Lastly, we show that epigenetic conservation combined with sequence similarity helps uncover functionalcis-regulatory elements and enhances our ability to interpret genetic variants contributing to neurological disease and traits.