Biology subjects

Guo, J.

Publications and source records attributed to Guo, J..

At least 235 records · Page 13Linked to original sources

bioRxiv2023

The mechanosensitive ion channel Piezo1 contributes to ultrasound neuromodulation

Transcranial low-intensity ultrasound is a promising neuromodulation modality, with the advantages of non-invasiveness, deep penetration, and high spatiotemporal accuracy. However, the underlying biological mechanism of ultrasonic neuromodulation remains unclear, hindering the development of efficacious treatments. Here, the well-known Piezo1, was studied through a conditional knockout mouse model as a major molecule for ultrasound neuromodulation ex vivo and in vivo. We showed that Piezo1 knockout in the right motor cortex of mice significantly reduced ultrasound-induced neuronal calcium responses, limb movement and muscle EMG responses. We also detected higher Piezo1 in the central amygdala (CEA) which were found more sensitive to ultrasound stimulation than that of cortex. Knocking out the Piezo1 in CEA neurons showed a significant reduction of response under ultrasound stimulation while knocking out astrocytic Piezo1 showed no obvious changes in neuronal responses. Additionally, we excluded an auditory confound by monitoring auditory cortical activation and using smooth waveform ultrasound with randomized parameters to stimulate P1KO ipsilateral and contralateral regions of the same brain and recording evoked movement in the corresponding limb. Thus, we demonstrate that Piezo1 is functionally expressed in different brain regions, and that it is an important mediator of ultrasound neuromodulation in the brain, laying the ground for further mechanistic studies of ultrasound.

neuroscience↗

bioRxiv2023

ASTK: a software for comprehensive analysis of alternative splicing

Alternative splicing (AS) is a fundamental mechanism that regulates gene expression. Splicing dynamics is involved in both physiological and pathological processes. In this paper, we introduce ASTK, a software package covering upstream and downstream analysis of AS. Initially, ASTK offers a module to perform enrichment analysis at both the gene- and exon-level to incorporate various impacts by different spliced events on a single gene. We further cluster AS genes and alternative exons into three groups based on spliced exon sizes (micro-, mid-, and macro-), which are preferentially associated with distinct biological pathways. A major challenge in the field has been decoding the regulatory codes of splicing. ASTK adeptly extracts both sequence features and epigenetic marks associated with AS events. Through the application of machine learning algorithms, we identified pivotal features influencing the inclusion levels of most AS types. Notably, the splice site strength is a primary determinant for the inclusion levels in alternative 3/5 splice sites (A3/A5). For the alternative first exon (AF) and skipping exon (SE) classes, a combination of sequence and epigenetic features collaboratively dictate exon inclusion/exclusion. Our findings underscore ASTKs capability to enhance the functional understanding of AS events and shed light on the intricacies of splicing regulation.

bioinformatics↗

bioRxiv2022

Accuracy of functional gene community detection in Saccharomyces cerevisiae by maximizing Generalized Modularity Density

Identifying functionally-cohesive gene communities from large data sets of expression data for individual genes is a key approach to understanding the molecular components of biological processes. Here, we compare the accuracy of twelve different approaches to infer gene co-expression networks and then find gene communities within the networks. Among the approaches used are ones involving a recently developed clustering method that identifies communities by maximizing Generalized Modularity Density (Qg). RNA-Seq data from 691 samples of S. cerevisiae (yeast) are analyzed. These data have been obtained from organisms grown under diverse environmental and developmental conditions and encompass varied mutant lines. To assess the accuracy of different approaches, we introduce a statistical measure, the Average Adjusted Rand Index (AARI) score, which compares their results to Gene Ontology (GO) term associations. Inferring gene networks using the Context Likelihood of Relatedness (CLR) and subsequently clustering by maximizing Generalized Modularity Density is found to identify the most significant functional communities. Also, to quantify the extent to which the identified communities are biologically relevant, a GO term enrichment analysis is performed. The results indicate that many of the communities found by maximizing Generalized Modularity Density are enriched in genes with known biological functions. Furthermore, some of the communities contain genes of unknown function, enabling inference of potentially novel functional interactions involving these genes. Furthermore, some genes are species-specific orphan genes; assignment of these orphan genes to communities enriched in a particular biological process provides a method to infer the biological process in which they are involved. We focus on a few communities that are highly significantly enriched in a particular biological process, and develop experimentally-testable predictions about the orphan genes in these communities. Author summaryFinding gene communities that are of biological relevance from expression profiles of individual genes is a critical approach to understanding biological processes and their molecular components. Various computational methods have been developed to infer underlying metabolic and regulatory networks and to identify functional communities of genes. Which network inference and clustering methods works best to achieve this goal has largely remained an open question. Here, using genome-wide transcriptomic data for S. cerevisiae, we systematically compare the effectiveness of several commonly used network inference and clustering methods. We rank these methods by comparing the clusters obtained by different methods to Gene Ontology (GO) terms. We find that inferring gene networks using a method known as the Context Likelihood of Relatedness (CLR) and subsequently clustering by maximizing Generalized Modularity Density identifies the most significant functional communities.

systems biology↗

bioRxiv2022

Biosynthesis of Kratom Opioids

Mitragyna speciosa (kratom) derived monoterpenoid indole alkaloids (MIAs) such as mitragynine and 7-hydroxymitragynine are a new class of opioids with a corynanthe MIA pharmacophore that is responsible for their significantly reduced side effects and superior safety profiles. While botanical kratom has been historically used for stimulation and pain management in Southeast Asia, the biosynthesis of kratom MIAs is not known. In this study, we identified and characterized 9 reductases bearing various degrees of demethyldihydrocoryanthine/demethylcorynantheidine synthase activity and a new SABATH type methyltransferase that catalyzes highly unusual non-aromatic enol methylation from kratom and several other species, which are required in kratom opioids biosynthesis. With unnatural substrate 4-hydroxytryptamine, we further showed the biosynthesis of mitragynine and its epimer speciogynine using these characterized enzymes. The promiscuity of kratom opioid biosynthetic enzymes suggests that derivatives and analogs of kratom opioids may be manufactured in heterologous systems with appropriate enzymes and substrates.

biochemistry↗

bioRxiv2022

PD-L1 regulates inflammatory macrophage development from human pluripotent stem cells by maintaining interferon-gamma signal

PD-L1 (programmed death-ligand 1) serves as a pivotal immune checkpoint in both the innate and adaptive immune systems. PD-L1 is expressed in macrophages in response to interferon-gamma (IFN{gamma}). We examined whether PD-L1 might regulate macrophage development. We established PD-L1-/- human pluripotent stem cells, differentiated them into macrophages, and observed a 60% reduction of CD11B+CD45+ macrophages in PD-L1-/-, orthogonally verified with PD-L1 inhibitor BMS-1166 reduced macrophages to the same fold. Single-cell RNA sequencing further confirmed the 60% reduction of macrophages as well as the down-regulation of macrophage-defining transcription factors SPI1, KLF6, and MAFB. Further, PD-L1-/- macrophages reduced the level of inflammatory signals such as NF{kappa}B, TNF, and chemokines CXCL and CCL families. Whilst anti-inflammatory TGF-{beta} was upregulated. Finally, we identified that PD-L1-/- macrophages significantly down-regulated interferon-stimulated genes (ISGs) despite IFN{gamma} in differentiation media. Mechanistically, PD-L1-/- macrophages reduced IFNGR1 expression explaining that cells could not respond to IFN{gamma}. These data suggest that PD-L1 regulates inflammatory macrophage development by maintaining the IFN{gamma} signal.

immunology↗

bioRxiv2022

The nutrient-sensing GCN2 signaling pathway is essential for circadian clock function by regulating histone acetylation under amino acid starvation

Circadian clocks are evolved to adapt to the daily environment changes under different conditions. The ability to maintain circadian clock functions in response to various stress and perturbations is important for organismal fitness. Here, we show that the nutrient sensing GCN2 signaling pathway is required for robust circadian clock function under amino acid starvation in Neurospora. The deletion of GCN2 pathway components disrupts rhythmic transcription of clock gene frq by suppressing WC complex binding at the frq promoter due to its reduced histone H3 acetylation levels. Under amino acid starvation, the activation of GCN2 kinase and its downstream transcription factor CPC-1 establish a proper chromatin state at the frq promoter by recruiting the histone acetyltransferase GCN-5. The arrhythmic phenotype of the GCN2 kinase mutants under amino acid starvation can be rescued by inhibiting histone deacetylation. Finally, genome-wide transcriptional analysis indicates that the GCN2 signaling pathway maintains robust rhythmic expression of metabolic genes under amino acid starvation. Together, these results uncover an essential role of GCN2 signaling pathway in maintaining robust circadian clock function in response to amino acid starvation and the importance of histone acetylation at the frq locus in rhythmic gene expression.

genetics↗

bioRxiv2022

Hierarchical Modular Structure of the Drosophila Connectome

The structure of neural circuitry plays a crucial role in brain function. Previous studies of brain organization generally had to trade off between coarse descriptions at a large scale and fine descriptions on a small scale. Researchers have now reconstructed tens to hundreds of thousands of neurons at synaptic resolution, enabling investigations into the interplay between global, modular organization, and cell type-specific wiring. Analyzing data of this scale, however, presents unique challenges. To address this problem we applied novel community detection methods to analyze the synapse-level reconstruction of an adult fruit fly brain containing over 20 thousand neurons and 10 million synapses. Using a machine-learning algorithm, we find the most densely connected communities of neurons by maximizing a generalized modularity density measure. We resolve the community structure at a range of scales, from large (on the order of thousands of neurons) to small (on the order of tens of neurons). We find that the network is organized hierarchically and larger-scale communities are composed of smaller-scale structures. Our methods identify well-known features of the fly brain, including its sensory pathways. Moreover, focusing on specific brain regions, we are able to identify subnetworks with distinct connectivity types. For example, manual efforts have identified layered structures in the fan-shaped body. Our methods not only automatically recover this layered structure, but also resolve finer connectivity patterns to downstream and upstream areas. We also find a novel modular organization of the superior neuropil, with distinct clusters of upstream and downstream brain regions dividing the neuropil into several pathways. These methods show that the fine-scale, local network reconstruction made possible by modern experimental methods are sufficiently detailed to identify the organization of the brain across scales, and enable novel predictions about the structure and function of its parts.

neuroscience↗

bioRxiv2022

Organism-wide secretome mapping uncovers pathways of tissue crosstalk in exercise

There has been growing interest in identifying blood-borne factors that mediate tissue crosstalk and function as molecular effectors of physical activity. Although past studies have focused on an individual molecule or cell type, the organism-wide secretome response to physical activity has not been evaluated. Here, we use a cell type-specific proteomic approach to generate a 21-cell type, 10-tissue map of exercise-regulated secretomes in mice. Our dataset identifies >200 exercise-regulated cell type-secreted protein pairs, the majority of which have not been previously reported. Pdgfra-cre-labeled secretomes were the most responsive to exercise training. Elevated lactate levels can directly regulate protein secretion. Lastly, we establish an anti-obesity and anti-diabetic role for a proteoform of an intracellular carboxylesterase whose secretion from the liver is induced by exercise training. Together, our data uncover the dynamic remodeling of cell and tissue crosstalk by physical activity.

systems biology↗

bioRxiv2022

Human Early Syncytiotrophoblasts Are Highly Susceptible to SARS-CoV-2 Infection

The ongoing and devastating pandemic of coronavirus disease 2019 (COVID-19) has led to a global public health crisis. COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and can potentially pose a serious risk to maternal and neonatal health. Cases of abnormal pregnancy and vertical transmission of SARS-CoV-2 from mother to foetus have been reported but no firm conclusions are drawn. Trophoblasts are the major constituents of the placenta to protect and nourish the developing foetus. However, direct in vivo investigation of trophoblasts susceptibility to SARS-CoV-2 and of COVID-19 and pregnancy is challenging. Here we report that human early syncytiotrophoblasts (eSTBs) are highly susceptible to SARS-CoV-2 infection in an angiotensin-converting enzyme 2 (ACE2)-dependent manner. From human expanded potential stem cells (hEPSCs), we derived bona fide trophoblast stem cells (TSCs) that resembled those originated from the blastocyst and the placenta in generating functional syncytiotrophoblasts (STBs) and extravillus trophoblasts (EVTs) and in low expression of HLA-A/B and amniotic epithelial (AME) cell signature. The EPSC-TSCs and their derivative trophoblasts including trophoblast organoids could be infected by SARS-CoV-2. Remarkably, eSTBs expressed high levels of ACE2 and produced substantially higher amounts of virion than Vero E6 cells which are widely used in SARS-CoV-2 research and vaccine production. These findings provide experimental evidence for the clinical observations that opportunistic SARS-CoV-2 infection during pregnancy can occur. At low concentrations, two well characterized antivirals, remdesivir and GC376, effectively eliminated infection of eSTBs by SARS-CoV-2 and middle east respiratory syndrome-related coronavirus (MERS-CoV), and rescued their developmental arrest caused by the virus infection. Several human cell lines have been used in coronavirus research. However, they suffer from genetic and/or innate immune defects and have some of the long-standing technical challenges such as cell transfection and genetic manipulation. In contrast, hEPSCs are normal human stem cells that are robust in culture, genetically stable and permit efficient gene-editing. They can produce and supply large amounts of physiologically relevant normal and genome-edited human cells such as eSTBs for isolation, propagation and production of coronaviruses for basic research, antivirus drug tests and safety evaluation.

cell biology↗

bioRxiv2022

Chaperones Hsc70 and Hsp70 Play Distinct Roles in Bocaparvovirus Minute Virus of Canines Infection

Minute virus of canines (MVC) belongs to the genus Bocaparvovirus and reproduces rapidly in its permissive cells Walter Reed/3873D (WRD). The crosstalk between MVC and WRD is poorly characterized in terms of molecular requirements and mechanisms. Here, we identified two novel cellular proteins Hsc70 and Hsp70 that interact with both NS1 and VP2 via mass spectrometry (MS), co-immunoprecipitation (Co-IP) and confocal immunofluorescence assays (IFA). Hsp70 was upregulated upon MVC infection. Respective silencing of Hsc70 and Hsp70 led to contrasting results at nearly every stage of MVC life cycle, including virus entry, transcription, translation, replication and production. Strikingly, transfection with low and high dose of pFlag-Hsp70 contributed to opposing impacts on viral protein levels and virus production possibly through a ubiquitin-dependent manner, indicating that MVC is quite sensitive to the levels of Hsp70. Treatment with quercetin and VER155008, two Hsp70 family inhibitors, both significantly decreased viral replication and particle levels. Together, these results illustrated that both Hsc70 and Hsp70 are involved in MVC life cycle, and targeting to Hsp70 family may represent a novel anti-MVC mechanism.

molecular biology↗

bioRxiv2022

Inflammation-mediated Upregulation of VCAM-1 but not KIM-1 during Acute Kidney Injury to Chronic Kidney Disease Transition

BackgroundPatients with acute kidney injury (AKI) have higher risks of developing chronic kidney disease (CKD). The basis for the AKI-to-CKD transition remains poorly understood, but studies in animal models suggest a linkage between the inflammatory response to injury and subsequent nephron loss and interstitial fibrosis. The proximal tubule is the primary venue of injury and progression of disease during this process. MethodsMouse unilateral ischemia/reperfusion injury (U-IRI) model was used to study the kinetics of proximal injury marker expression during AKI-to-CKD transition. Immortalized MPT cells and primary cultured renal cells were used to study factor(s) that induce vascular cell adhesion protein-1 (VCAM-1) expression in proximal tubule cells. ResultsKidney injury molecule-1 (KIM-1) was rapidly upregulated on day 1 after injury and gradually reduced close to the baseline; whereas VCAM-1 was not upregulated on day 1 but markedly increased afterwards during AKI-to-CKD transition. The proximal tubular VCAM-1 expression is induced by proinflammatory cytokines including TNF and IL-1{beta}. Blockade of these signaling pathways by using NF-{kappa}B inhibitor or by using double null mutant Myd88 and Trif derived PCRC in vitro or decrease of immune cell recruitment using Ccr2 null mouse in vivo significantly suppressed VCAM-1 expression. Human single cell transcriptome analysis identified a distinct cluster of injured proximal tubules that highly expressed VCAM1 but not HAVCR1 (KIM1), and the population of these VCAM1-positive proximal tubule cells was associated with CKD progression and VCAM-1 levels were significantly higher in the patients with Stage 3 CKD as compared to the healthy references. ConclusionsProximal tubule cells upregulated KIM-1 and VCAM-1 in an orchestrated fashion after injury. Upregulation of VCAM-1 associated with chronic tubular injury and interstitial fibrosis and may mark the earliest molecular event during AKI-to-CKD transition.

pathology↗

bioRxiv2022

Magnetic Resonance Spectroscopy Spectral Registration Using Deep Learning

A novel convolutional neural network based spectral registration (CNN-SR) approach is introduced to achieve efficient and accurate simultaneous frequency-and-phase correction (FPC) of single-voxel MEGA-PRESS magnetic resonance spectroscopy (MRS) data. For this approach, one neural network was trained and validated using a published simulated and in vivo MEGA-PRESS MRS dataset with a wide-range of artificial frequency (0-20 Hz) and phase (0-90{degrees}) offsets applied. The proposed CNN-SR approach was subsequently tested and compared to the sequential FPC deep learning approaches and demonstrated more effective and accurate performance. Furthermore, a large random Gaussian signal-to-noise ratio (SNR 20 and SNR 2.5) and line broadening (0-20 ms) was introduced to the original simulated dataset to investigate our model performance compared to the other deep learning models. The testing showed that CNN-SR was a more accurate quantification tool and resulted in a lower SNR when compared with the other deep learning methods, due to having smaller mean absolute errors in both frequency and phase offset predictions. For Off spectra, the CNN-SR model was capable of correcting frequency offsets with 0.014 {+/-} 0.010 Hz and phase offsets with 0.104 {+/-} 0.076{degrees} absolute errors on average for unseen simulated data with SNR 20 and correcting frequency offsets with 0.678 {+/-} 0.883 Hz and phase offsets with 2.367 {+/-} 2.616{degrees} absolute errors on average at very low SNR (2.5) and line broadening (0-20 ms) introduced. In addition, we tested the simulated dataset with additional SNR and line broadening on a more refined model (CNN-SR+) where the pre-trained CNN-SR was further optimized by minimizing the difference between individual spectra and a common template with unsupervised learning. The performance on Off spectra was improved to 0.058 {+/-} 0.050 Hz for correcting frequency offsets and to 0.416 {+/-} 0.317{degrees} for correcting phase offsets. We further evaluated the ability of our model to process the published Big GABA in vivo dataset and CNN-SR+ achieved the best performance. Moreover, additional frequency and phase offsets (i.e., small, moderate, large) were applied to the in vivo dataset, and CNN-SR+ also demonstrated better performance for FPC when compared to the other deep learning models. These results indicate the utility of using deep learning for spectral registration and demonstrate the application of unsupervised learning in further improving the model to achieve state-of-the-art performance.

neuroscience↗

bioRxiv2022

The western redcedar genome reveals low genetic diversity in a self-compatible conifer

We assembled the 9.8 Gbp genome of western redcedar (WRC, Thuja plicata), an ecologically and economically important conifer species of the Cupressaceae. The genome assembly, derived from a uniquely inbred tree produced through five generations of self-fertilization (selfing), was determined to be 86% complete by BUSCO analysis - one of the most complete genome assemblies for a conifer. Population genomic analysis revealed WRC to be one of the most genetically depauperate wild plant species, with an effective population size of approximately 300 and no significant genetic differentiation across its geographic range. Nucleotide diversity, {pi}, is low for a continuous tree species, with many loci exhibiting zero diversity, and the ratio of {pi} at zero-to four-fold degenerate sites is relatively high ([~] 0.33), suggestive of weak purifying selection. Using an array of genetic lines derived from up to five generations of selfing, we explored the relationship between genetic diversity and mating system. While overall heterozygosity was found to decline faster than expected during selfing, heterozygosity persisted at many loci, and nearly 100 loci were found to deviate from expectations of genetic drift, suggestive of associative overdominance. Non-reference alleles at such loci often harbor deleterious mutations and are rare in natural populations, implying that balanced polymorphisms are maintained by linkage to dominant beneficial alleles. This may account for how WRC remains responsive to natural and artificial selection, despite low genetic diversity.

plant biology↗

bioRxiv2022

Hydrogel Assisted Double Molding of 3D-Print Enables Prestress Regulation of Micro-Heart Muscle Physiology

Engineered heart tissues have been created to study cardiac biology and disease in a setting that more closely mimics in-vivo heart muscle than 2D monolayer culture. Previously published studies suggest that geometrically anisotropic micro-environments are crucial for inducing "in vivo-like" physiology from immature cardiomyocytes. We hypothesized that such anisotropic tissue geometries regulate tissue prestress, and that in turn this prestress is a major factor regulating cardiomyocytes electrophysiological development. Thus, we studied the effects of tissue geometry on electrophysiology of micro-heart muscle arrays (HM) engineered from human induced pluripotent stem cells (iPSC). Geometries predicted to increase tissue prestress not only affected cardiomyocyte structure, but also had profound effects on electrophysiology. Elongated geometries led to adaptations that yielded increased calcium intake during each contraction cycle. Strikingly, pharmacologic studies revealed a prestress threshold is required for sodium channel function, whereas L-type calcium and rapidly-rectifying potassium channels were largely insensitive. Analysis of RNA and protein levels suggest sodium channel activity changes were related to post-transcriptional, and potentially post-translational, changes. HM formed from Plakophilin 2 (PKP2) knockout iPSC had a cellular structure similar to isogenic controls. However, these tissues exhibited no functional sodium current and an overall lesser degree of electrical remodeling in response to prestress. These results suggest that PKP2, a key component of the nascent desmosome, is crucial to transducing tissue prestress into physiologically beneficial electrical remodeling via activation of sodium channels.

bioengineering↗

bioRxiv2022

Divergent evolution of early terrestrial fungi reveals the evolution of Mucormycosis pathogenicity factors

Fungi have evolved over millions of years and their species diversity is predicted to be the second largest on the earth. Fungi have cross-kingdom interactions with many organisms which have mutually shaped their evolutionary trajectories. Zygomycete fungi hold a pivotal position in the fungal tree of life and provide important perspectives on the early evolution of fungi from aquatic to terrestrial environments. Phylogenomic analyses have found that zygomycete fungi diversified into two separate clades, the Mucoromycota which are frequently associated with plants and Zoopagomycota that are commonly animal-associated fungi. Genetic elements that contributed to the fitness and divergence of these lineages may have been shaped by the varied interactions these fungi have had with plants, animals, bacteria and other microbes. To investigate this, we performed comparative genomic analyses of the two clades in the context of Kingdom Fungi, benefiting from our generation of a new collection of zygomycete genomes. We identified lineage-specific genomic content which may contribute to the disparate biology observed in these zygomycetes. Our findings include the discovery of undescribed diversity in CotH, a Mucormycosis pathogenicity factor, which was found in a broad set of zygomycetes. Reconciliation analysis identified multiple duplication events and an expansion of CotH copies throughout Mucoromycotina, Mortierellomycotina, Neocallimastigomycota, and Basidiobolus lineages. A kingdom-level phylogenomic analysis also identified new evolutionary relationships within the sub-phyla of Mucoromycota and Zoopagomycota.

evolutionary biology↗

bioRxiv2022

The mechanosensitive ion channel Piezo1 modulates the migration and immune response of microglia

Microglia are the brains resident immune cells, performing surveillance to promote homeostasis and healthy functioning. While chemical signaling in microglia is well-studied, the mechanical cues regulating their function are less well-understood. Here, we investigate the role of the mechanosensitive ion channel Piezo1 in microglia migration, pro-inflammatory cytokine production and stiffness sensing. We demonstrated the functional expression of Piezo1 in microglia and identified genes whose expression was affected by conditional Piezo1 knockout in transgenic mice. Functional assays revealed that Piezo1-deficiency in microglia enhanced migration towards amyloid {beta}-protein, and decreased levels of pro-inflammatory cytokines produced upon stimulation by lipopolysaccharide, both in vitro and in vivo. The phenomenon could be mimicked or reversed using a Piezo1-specific agonist or antagonist. Finally, we also showed that Piezo1 mediated the effect of substrate stiffness-induced migration and cytokine expression. Altogether, we show that Piezo1 is an important molecular mediator for microglia, its activation modulating their migration and immune responses.

neuroscience↗

bioRxiv2022

Triangulation fails when neither linguistic, genetic, nor archaeological data support the Transeurasian narrative

Robbeets et al.1 argue that the dispersal of the so-called "Transeurasian" languages, a highly disputed language superfamily comprising the Turkic, Mongolian, Tungusic, Koreanic, and Japonic language families, was driven by Neolithic farmers in the West Liao River region of China. They adduce evidence from linguistics, archaeology, and genetics to support their claim. An admirable feature of the Robbeets et al.s paper is that all their datasets can be accessed. However, a closer investigation of all three types of evidence reveals fundamental problems with each of them. Robbeets et al.s analysis of the linguistic data does not conform to the minimal standards required by traditional scholarship in historical linguistics and contradicts their own stated sound correspondence principles. A reanalysis of the genetic data finds that they do not conclusively support the farming-driven dispersal of Turkic, Mongolian, and Tungusic, nor the two-wave spread of farming to Korea. Their archaeological data contain little phylogenetic signal, and we failed to reproduce the results supporting their core hypotheses about migrations. Given the severe problems we identify in all three parts of the "triangulation" process, we conclude that there is neither conclusive evidence for a Transeurasian language family nor for associating the five different language families with the spread of Neolithic farmers from the West Liao River region.

genetics↗

bioRxiv2022

Immune-mediated Tubule Atrophy Promotes Acute Kidney Injury to Chronic Kidney Disease Transition

Incomplete repair after acute kidney injury (AKI) is associated with progressive loss of tubular cell function and development of chronic kidney disease (CKD). Here, we compared mice subjected to either unilateral ischemia-reperfusion kidney injury with contralateral nephrectomy (IRI/CL-NX, in which tubule repair predominates) or unilateral IRI with contralateral kidney intact (U-IRI, in which fibrosis and atrophy predominates) to investigate the mechanism(s) underlying transition to CKD following AKI. The initial injury and early recruitment and activation of macrophages, dendritic cells (DCs), neutrophils, and T cells were similar through day 7 but markedly diverged afterwards between the two models. By day 14, kidneys subjected to U-IRI had greater numbers of macrophages with higher expression of Ccl2, Ccl7, Ccl8, Ccl12, and Cxcl16. These chemokines correlated with a second wave of Ccr1-positive neutrophils and Cxcr6-positive T cells, resulting in a proinflammatory milieu, accompanied by increased expression of tubular cell injury, oxidative stress and major histocompatibility complex genes. This second wave of immune dysfunction led to a distinct profile of tubule injury with morphologic kidney atrophy and a decreased proportion of differentiated tubule cells. Combined depletion of neutrophils and T cells beginning on day 5 after U-IRI was found to reduce tubular cell loss and the associated kidney atrophy. In kidney biopsy samples from patients with AKI, the number of interstitial T cells and neutrophils negatively correlated with 6-month recovery of GFR. Together, our findings demonstrate that macrophage persistence after AKI promotes a T cell- and neutrophil-mediated proinflammatory milieu that leads to progressive tubule damage.

pathology↗