Biology subjects

Tang, Y.

Publications and source records attributed to Tang, Y..

At least 199 records · Page 11Linked to original sources

bioRxiv2023

Spatiotemporal transcriptome atlas of human embryos after gastrulation

The spatial and temporal atlas of gene expression in the human embryo at early gestation is critical in understanding embryo development, organogenesis, and disease origins. We obtained the spatiotemporal transcriptome from 90 sagittal sections of 16 whole human embryos from 3 to 8 post-conception weeks by Stereo-seq with high resolution and ultra-large field, establishing the development trajectory/regulatory profiling of 49 organs. We uncovered the organ-specific regulons as potential lineage-determining factors and identified the new regulatory networks during heart and brain development. The atlas refines the key organs/cell types vulnerable to virus infection and genetic disorders, and, reveals the dynamics of allelic gene expression in specific organs at different stages. These results present the first comprehensive delineation of the spatiotemporal transcriptomic dynamics of human organogenesis. One Sentence SummaryThe spatiotemporal transcriptome atlas presents a comprehensive delineation of human embryogenesis after gastrulation.

developmental biology↗

bioRxiv2023

Protein language model-based end-to-end type II polyketide prediction without sequence alignment

Natural products are important sources for drug development, and the precise prediction of their structures assembled by modular proteins is an area of great interest. In this study, we introduce DeepT2, an end-to-end, cost-effective, and accurate machine learning platform to accelerate the identification of type II polyketides (T2PKs), which represent a significant portion of the natural product world. Our algorithm is based on advanced natural language processing models and utilizes the core biosynthetic enzyme, chain length factor (CLF or KS{beta}), as computing inputs. The process involves sequence embedding, data labeling, classifier development, and novelty detection, which enable precise classification and prediction directly from KS{beta} without sequence alignments. Combined with metagenomics and metabolomics, we evaluated the ability of DeepT2 and found this model could easily detect and classify KS{beta} either as a single sequence or a mixture of bacterial genomes, and subsequently identify the corresponding T2PKs in a labeled categorized class or as novel. Our work highlights deep learning as a promising framework for genome mining and therefore provides a meaningful platform for discovering medically important natural products.

evolutionary biology↗

bioRxiv2023

BayFlux: A Bayesian method to quantify metabolic Fluxes and their uncertainty at the genome scale

Metabolic fluxes, the number of metabolites traversing each biochemical reaction in a cell per unit time, are crucial for assessing and understanding cell function. 13C Metabolic Flux Analysis (13C MFA) is considered to be the gold standard for measuring metabolic fluxes. 13C MFA typically works by leveraging extracellular exchange fluxes as well as data from 13C labeling experiments to calculate the flux profile which best fit the data for a small, central carbon, metabolic model. However, the nonlinear nature of the 13C MFA fitting procedure means that several flux profiles fit the experimental data within the experimental error, and traditional optimization methods offer only a partial or skewed picture, especially in "non-gaussian" situations where multiple very distinct flux regions fit the data equally well. Here, we present a method for flux space sampling through Bayesian inference (BayFlux), that identifies the full distribution of fluxes compatible with experimental data for a comprehensive genome-scale model. This Bayesian approach allows us to accurately quantify uncertainty in calculated fluxes. We also find that, surprisingly, the genome-scale model of metabolism produces narrower flux distributions (reduced uncertainty) than the small core metabolic models traditionally used in 13C MFA. The different results for some reactions when using genome-scale models vs core metabolic models advise caution in assuming strong inferences from 13C MFA since the results may depend significantly on the completeness of the model used. Based on BayFlux, we developed and evaluated novel methods (P-13C MOMA and ROOM) to predict the biological results of a gene knockout, that improve on the traditional MOMA and ROOM methods. We provide an open source Python implementation of BayFlux at https://github.com/JBEI/bayflux. Author summary13C MFA practitioners know that modeling results can be sensitive to minor modifications of the metabolic model. Certain parts of the metabolic model that are not well mapped to a molecular mechanism (e.g. drains to biomass or ATP maintenance) can have an inordinate impact on the final fluxes. The only way to ascertain the validity of the model is by checking that the result does not significantly differ from previously observed flux profiles. However, that approach diminishes the possibility of discovering truly novel flux profiles. Because of this strong dependence on metabolic model details, it would be very useful to have a systematic and repeatable way to produce these metabolic models. And indeed there is one: genome-scale metabolic models can be systematically obtained from genomic sequences, and represent all the known genomically encoded metabolic information. However, these models are much larger than the traditionally used central carbon metabolism models. Hence, the number of degrees of freedom of the model (fluxes) significantly exceeds the number of measurements (metabolite labeling profiles and exchange fluxes). As a result, one expects many flux profiles compatible with the experimental data. The best way to represent these is by identifying all fluxes compatible with the experimental data. Our novel method BayFlux, based on Bayesian inference and Markov Chain Monte Carlo sampling, provides this capability. Interestingly, this approach leads to the observation that traditional optimization approaches can significantly overestimate flux uncertainty, and that genome-scale models of metabolism produce narrower flux distributions than the small core metabolic models that are traditionally used in 13C MFA. Furthermore, we show that the extra information provided by this approach allows us to improve knockout predictions, compared to traditional methods. Although the method scales well with more reactions, improvements will be needed to tackle the large metabolic models found in microbiomes and human metabolism.

systems biology↗

bioRxiv2023

Cortical gradient perturbation in attention deficit hyperactivity disorder correlates with neurotransmitter-, cell type-specific and chromosome- transcriptomic signatures

Neurofunctional dysregulations in spatially discrete areas or isolated pathways have been suggested as neural markers for attention deficit hyperactivity disorder (ADHD). However, multiscale perspectives into the neurobiological underpins of ADHD spanning multiple biological systems remain sparse. This points to the need of multi-levels of analysis encompassing brain functional organization and its correlation with molecular and cell-specific transcriptional signatures are stressed. Here, we capitalized on diffusion mapping embedding model to derive the functional connectome gradient, and deployed multivariate partial least square (PLS) method to uncover the enrichment of neurotransmitomic, cellular and chromosomal connectome-transcriptional signatures of ADHD. Compared to typical control, ADHD children presented connectopic cortical perturbations in lateral orbito-frontal and superior temporal regions, which had also been validated in another independent sample. This gradient-derived variants in ADHD further aligned spatially with distributions of GABAA/BZ and 5-HT2A receptors and co-varied with genetic transcriptional expression. Cognitive decoding and gene-expression annotation showed the correlates of these variants in memory, emotional regulation and spatial attention. Moreover, the gradient-derived transcriptional signatures of ADHD exhibited enriched expression of oligodendrocyte precursors and endothelial cells, and were mainly involved as variants of chromosome 18, 19 and X. In conclusion, our findings bridged in-vivo neuroimging assessed functional brain organization patterns to a multi-level molecular pathway in ADHD, possibly shedding light on the interrelation of biological systems that may coalesce to the emergence of this disorder.

neuroscience↗

bioRxiv2023

Micropolarity governs the structural organization of biomolecular condensates

Microenvironment is critical to the function of cells and organisms. One example is provided by biomolecular condensates, whose microenvironment can be vastly different from the surrounding cellular environments to engage unique biological functions. How microenvironments of biomolecular condensates affect their structure and function remains unknown. Here, we show that the arrangements and partitioning of biomolecules are dictated by the differences between the micropolarity of each subcompartment. Sufficient difference in micropolarity results in layered structures with the exterior shell presenting a more polar microenvironment than the interior core. Accordingly, micropolarity inversion is accompanied by conversions of the layered structures. These findings demonstrated the central role of the previously overlooked microenvironment in regulating the structural organization and function of membraneless organelles.

biochemistry↗

bioRxiv2023

Multi-omics and Pharmacological Characterization of Patient-derived Glioma Cell Lines

Glioblastoma (GBM) is the most common brain tumor and is currently incurable. Primary GBM cultures are widely used tools for screening potentially therapeutic drugs; however, there is a lack of genomic and pharmacological characterization of these primary GBM cultures. Here, we collected 52 patient-derived glioma cell (PDGC) lines and characterized them through whole- genome sequencing (WGS), RNA-seq, and drug response screening. We identified three molecular subtypes among PDGCs: mesenchymal (MES), proneural (PN), and oxidative phosphorylation (OXPHOS). Upon profiling the responses of PDGCs to 214 drugs, we found that the PN subtype PDGCs were sensitive to tyrosine kinase inhibitors, whereas the OXPHOS subtype PDGCs were sensitive to histone deacetylase inhibitors, oxidative phosphorylation inhibitors, and HMG-CoA reductase inhibitors. PN and OXPHOS subtype PDGCs stably formed tumors in vivo upon intracranial transplantation into immunodeficient mice, while most MES subtype PDGCs were incapable of tumorigenesis in vivo. In addition, profiling and follow-up investigations showed that the serum-free culture system used for PDGCs enriched and propagated rare MYC/MYCN- amplified glioma cells. Our study provides a resource for understanding primary glioma cell cultures and aiding clinical translation. SignificanceOur study provides a resource for patient-derived glioma cell lines (PDGCs) on transcriptome, genome, drug response, and tumorigenic abilities. PDGCs are categorized into PN, MES, and OXPHOS subtypes, with MES-subtype PDGCs incapable of tumorigenesis in vivo. Notably, the serum-free culture system for PDGCs enriches glioma cells with MYC/MYCN amplification.

cancer biology↗

bioRxiv2023

Electroacupuncture prevents astrocyte atrophy to alleviate depression

Astrocyte atrophy is the main histopathological hallmark of the major depressive disorder (MDD) in humans and in animal models of depression. Here we show that electroacupuncture prevents astrocyte atrophy in the prefrontal cortex and alleviates depressive-like behaviour in mice subjected to the chronic unpredictable mild stress (CUMS). Treatment of mice with CUMS induced depressive-like phenotypes as confirmed by sucrose preference test, tail suspension test, and forced swim test. These behavioural changes were paralleled with morphological atrophy of astrocytes in the prefrontal cortex, revealed by analysis of 3D reconstructions of confocal Z-stack images of mCherry expressing astrocytes. This morphological atrophy was accompanied with a decrease in expression of cytoskeletal linker Ezrin, associated with formation of astrocytic leaflets, which form astroglial synaptic cradle. Electroacupuncture at the acupoint ST36 as well as treatment with anti-depressant fluoxetine prevented depressive-like behaviours, astrocytic atrophy and down-regulation of astrocytic ezrin. In conclusion, our data further strengthen the notion of a primary role of astrocytic atrophy in depression and reveal astrocytes as cellular target for electroacupuncture in treatment of depressive disorders.

neuroscience↗

bioRxiv2023

Mapping Neurophysiological Subtypes of Major Depressive Disorder Using Normative Models of the Functional Connectome

Major depressive disorder (MDD) is the most burdensome psychiatric disorder characterized by remarkably heterogeneous clinical phenotypes. It remains challenging to delineate the heterogeneity of neurobiological abnormalities underlying the clinical variance and, on this basis, to identify neurophysiological subtypes of MDD patients. Here, using a large multisite resting-state functional MRI data from 1,148 MDD patients and 1,079 healthy controls, we generated lifespan normative models of functional connectivity strengths, mapped the heterogeneity of patients individual deviations, and identified neurobiological MDD subtypes. MDD patients showed positive deviations mainly in the default mode and subcortical areas, and negative deviations widely distributed over the cortex. However, there was a great inter-subject heterogeneity as indicated by that no more than 3.14% of patients deviated from the normative range for any brain region. Two neurophysiological MDD subtypes were identified. Subtype 1 showed severe deviations with positive deviations in the default mode, limbic, and subcortical areas, and negative deviations in the sensorimotor, dorsal and ventral attention areas, while subtype 2 showed a moderate but conversed deviation pattern. The severe-deviation subtype had older age, higher medicated proportion, and higher Suicide item score, while the moderate-deviation subtype showed higher Work and Activities and Depressed Mood item scores. Moreover, the baseline deviations in the severe-deviation subtype were predictive of 6-month antidepressant treatment effects in a subsample. To our knowledge, the current study is the largest multisite analysis of neurophysiological MDD subtyping to date and the findings shed light on our understanding of the biological mechanisms underlying the intersubject heterogeneity of clinical phenotypes, which are informative for the development of personalized treatments for this disorder.

neuroscience↗

bioRxiv2023

Rigosertib promotes anti-tumor immunity via autophagic degradation of PD-L1 in colorectal cancer cells

Rigosertib (RGS) is a benzyl styryl sulfone which exhibits impressive cytotoxicity in cancer cells. However, its modulating effect on tumor immune microenvironment remains elusive. In our experiments, compared with immunodeficient mouse model, increased tumor growth arrest and robust anti-tumor immunity were observed in RGS-treated colorectal cancer (CRC) xenograft tumors in immunocompetent mice. Intriguingly, RGS markedly down-regulated programmed cell death ligand 1 (PD-L1) expression in both vivo and in vitro. Meanwhile, RGS increased autophagic vacuole number in CRC cells as seen by transmission electron microscopy and immunofluorescence. Moreover, increased LC3-II level and tandem- mRFP- GFP- LC3 labeled vacuole accumulation demonstrated RGS-induced autophagic flux. Mechanistically, it is the activation of AMP-activated protein kinase-UNC-51-like kinase 1 (AMPK-ULK1) axis, rather than the canonical mTOR signaling pathway, that plays a pivotal role in RGS-induced autophagy. AMPK-ULK1 dependent autophagy inhibition, by either short interfering RNA or chemical inhibitors, blocked RGS-induced PD-L1 degradation. Finally, RGS exhibited synergistic anti-tumor activity with cytotoxic T-lymphocyte-associated protein 4 monoclonal antibody in the CRC xenograft model. Furthermore, apart from the immunomodulatory effect, we also confirmed the direct cytotoxicity of RGS in inducing mitochondria-related apoptosis. Altogether, considering its PD-L1 inhibitory and cytotoxic effects, RGS could be a promising drug for CRC therapy.

cancer biology↗

bioRxiv2023

An Unexpected Role of Neutrophils in Clearing Apoptotic Hepatocytes In Vivo

Billions of apoptotic cells are removed daily in a human adult by professional phagocytes (e.g. macrophages) and neighboring nonprofessional phagocytes (e.g. stromal cells). Despite being a type of professional phagocyte, neutrophils are thought to be excluded from apoptotic sites to avoid tissue inflammation. Here we report a fundamental and unexpected role of neutrophils as the predominant phagocyte responsible for the clearance of apoptotic hepatic cells in the steady state. In contrast to the engulfment of dead cells by macrophages, neutrophils burrowed directly into apoptotic hepatocytes, a process we term perforocytosis, and ingested the effete cells from the inside. The depletion of neutrophils caused defective removal of apoptotic bodies, induced tissue injury in the mouse liver and led to the generation of autoantibodies. Human autoimmune liver disease showed similar defects in the neutrophil-mediated clearance of apoptotic hepatic cells. Hence, neutrophils possess a specialized immunologically silent mechanism for the clearance of apoptotic hepatocytes through perforocytosis, and defects in this key housekeeping function of neutrophils contribute to the genesis of autoimmune liver disease.

physiology↗

bioRxiv2023

Quorum sensing inhibits Type III-A CRISPR-Cas system activity through repressing positive regulators SarA and ArcR in Staphylococcus aureus

CRISPR-Cas is an adaptive immune system that protects prokaryotes from the invasion of foreign genetic elements. The components and immunity mechanisms of CRISPR-Cas have been extensively studied, but the regulation of this system in Staphylococci remains unclear. Here, we show that in the S. aureus Type III-A CRISPR-Cas system, the Pcas of 300 bp located in cas1 displays as a critical regulatory node that initiates the transcription of cas gene clusters. We discovered two transcriptional regulators, SarA and CRP-like ArcR, promote the expression and activity of the CRISPR-Cas system by directly binding to the novel promoter Pcas. Furthermore, we demonstrated that the cell-cell communication, known as quorum sensing (QS), inhibits the activity of CRISPR-Cas system by repressing the positive regulators SarA and ArcR. Bioinformatic analyses suggest that Pcas is conserved in many Type II and III CRISPR-Cas systems in Firmicutes. Our data reveal a new regulatory mechanism for QS-mediated repression of the Type III-A CRISPR-Cas system, which may allow S. aureus to acquire foreign genetic elements encoding antibiotic resistance or virulence factors specifically at high cell density.

microbiology↗

bioRxiv2023

Multifaceted roles of a light-responsive factor LhWRKY44 in promoting anthocyanin accumulation in Asiatic hybrid lilies (Lilium spp.)

The coloration of Asiatic hybrid lily results mostly from anthocyanin accumulation in flowers. Although anthocyanin accumulation-related genes and MBW complexes are well studied, the transcriptional regulation of WRKY transcription factors involved in anthocyanin accumulation remains poorly understood.Here, we identified a lily WRKY protein, LhWRKY44, whose expression is highly expressed downstream of LhHY5 by light and positively correlated with anthocyanin accumulation. LhWRKY44 overexpression enhanced anthocyanin accumulation and silencing decreased anthocyanin accumulation in flowers. As a trans-acting regulator, LhWRKY44 activited the anthocyanin biosynthesis pathway-related genes PAL and F3H by binding to the their promoters. And the encoded TF also participates in anthocyanin transport and targets the intracellular anthocyanin transport protein GST promoters. Additionally, a novel dual activity of LhWRKY44 and LhMYBSPLATTER regulatory module, with LhWRKY44 binds to the promoter of LhMYBSPLATTER and interacts with LhMYBSPLATTER, strongly enhanced the interaction of LhMYBSPLATTER and LhbHLH2, indirectly enhancing DFR, UFGT and GST expression targeted by LhMYBSPLATTER. These results show a regulatory mode for light-induced anthocyanin accumulation enhancement by LhWRKY44 in lily, expanding our understanding of the complex transcriptional regulatory hierarchy modulating anthocyanin accumulation.

molecular biology↗

bioRxiv2023

Gaudichaudione H inhibits Herpes Simplex Virus-1 replication by regulating cellular nuclear factor-κB in an interferon-γ-independent manner

The highly prevalent herpes simplex virus type 1 (HSV-1) causes keratoconjunctivitis and encephalitis. Viral DNA polymerase-inhibiting nucleoside analogs (such as acyclovir) are standard treatment agents against HSV infections but are limited by severe drug resistance issues. Thus, new antiviral agents with novel targets are urgently needed. Earlier, we investigated the anti-cancer, anti-inflammatory, and antibacterial bioactivities of Garcinia sp. Here, we report that non-cytotoxic concentrations (< 500 nM) of Gaudichaudione H (GH, isolated from Garcinia oligantha Merr.) potently inhibits HSV-1 replication in vitro without affecting viral entry or attachment. GH inhibits the expression of the viral proteins ICP0, ICP4, and ICP27 without affecting their mRNA levels. In Vero cells, GH enhanced STAT1 and 3 phosphorylation, which occurs downstream to interferon (IFN)-{gamma} activation during viral infections. However, pharmacological/genetic inhibition of IFN-{gamma} failed to suppress the GH-mediated inhibition of HSV-1 replication, indicating that GH exerts antiviral effects independent of IFN. Further mechanistic studies suggest that GH inhibits HSV-1 replication, at least partially by inhibiting cellular NF-{kappa}B activation. Moreover, GH prolonged the survival rate of KOS-infected mice by 25% (n = 5). In conclusion, GH treatment inhibits HSV-1 replication both in vitro and in vivo; therefore, it can be developed as an antiviral. ImportanceVery few therapeutic drug options are available to treat herpes simplex virus-1/2 which cause myriad debilitating diseases. We screened eight Garcinia compounds and found Gaudichaudione H was the most effective compound at non-cytotoxic concentrations. Further mechanism study illustrates that GH inhibits HSV-1 replication, at least partially by inhibiting cellular NF-{kappa}B activation. Natural compound is a promising resource of new antiviral agents with different targets that has ability to treat resistant viral strains.

cell biology↗

bioRxiv2023

High-throughput single molecule tracking identifies drug interactions and cellular mechanisms

The regulation of cell physiology depends largely upon interactions of functionally distinct proteins and cellular components. These interactions may be transient or long-lived, but often affect protein motion. Measurement of protein dynamics within a cellular environment, particularly while perturbing protein function with small molecules, may enable dissection of key interactions and facilitate drug discovery; however, current approaches are limited by throughput with respect to data acquisition and analysis. As a result, studies using super-resolution imaging are typically drawing conclusions from tens of cells and a few experimental conditions tested. We addressed these limitations by developing a high-throughput single-molecule tracking (htSMT) platform for pharmacologic dissection of protein dynamics in living cells at an unprecedented scale (capable of imaging > 106 cells/day and screening > 104 compounds). We applied htSMT to measure the cellular dynamics of fluorescently tagged estrogen receptor (ER) and screened a diverse library to identify small molecules that perturbed ER function in real time. With this one experimental modality, we determined the potency, pathway selectivity, target engagement, and mechanism of action for identified hits. Kinetic htSMT experiments were capable of distinguishing between on-target and on-pathway modulators of ER signaling. Integrated pathway analysis recapitulated the network of known ER interaction partners and suggested potentially novel, kinase-mediated regulatory mechanisms. The sensitivity of htSMT revealed a new correlation between ER dynamics and the ability of ER antagonists to suppress cancer cell growth. Therefore, measuring protein motion at scale is a powerful method to investigate dynamic interactions among proteins and may facilitate the identification and characterization of novel therapeutics.

cell biology↗

bioRxiv2022

Serine-129 phosphorylation of α-synuclein is a trigger for physiologic protein-protein interactions and synaptic function

Phosphorylation of -synuclein at the Serine-129 site (-syn Ser129P) is an established pathologic hallmark of synucleinopathies, and also a therapeutic target. In physiologic states, only a small fraction of total -syn is phosphorylated at this site, and consequently, almost all studies to date have focused on putative pathologic roles of this post-translational modification. We noticed that unlike native (total) -syn that is widely expressed throughout the brain, the overall pattern of -syn Ser129P is restricted, suggesting intrinsic regulation and putative physiologic roles. Surprisingly, preventing phosphorylation at the Ser-129 site blocked the ability of -syn to attenuate activity-dependent synaptic vesicle (SV) recycling - widely thought to reflect its normal function. Exploring mechanisms, we found that neuronal activity augments -syn Ser-129P, and this phosphorylation is required for -syn binding to VAMP2 and synapsin - two functional binding-partners that are necessary for -syn function. AlphaFold2-driven modeling suggests a scenario where Ser129P induces conformational changes in the C-terminus that stabilizes this region and facilitates protein-protein interactions. Our experiments indicate that the pathology-associated Ser129P is an unexpected physiologic trigger of -syn function, which has broad implications for pathophysiology and drug-development.

neuroscience↗

bioRxiv2022

Single-cell Sequencing Highlights Heterogeneity and Malignant Progression in Actinic Keratosis and Cutaneous Squamous Cell Carcinoma

Cutaneous squamous cell carcinoma (cSCC) is the second most frequent of the keratinocyte-derived malignancies with actinic keratosis (AK) as a precancerous lesion. To comprehensively delineate the underlying mechanisms for the whole progression from normal skin to AK to invasive cSCC, we performed single-cell RNA-seq (scRNA-seq) to acquire the transcriptomes of 138,982 cells from 13 samples of six patients including AK, squamous cell carcinoma in situ (SCCIS), cSCC and their matched normal tissues, covering comprehensive clinical courses of cSCC. We identified diverse cell types, including important subtypes with different gene expression profiles and functions in major keratinocytes. In SCCIS, we discovered the malignant subtypes of basal cells with differential proliferative and migration potential. Differentially expressed genes (DEGs) analysis screened out multiple key driver genes including transcription factors (TFs) along AK to cSCC progression. Immunohistochemistry (IHC) / immunofluorescence (IF) experiments and single-cell ATAC sequencing (scATAC-seq) data verified the expression changes of these genes. The functional experiments confirmed the important roles of these genes in regulating cell proliferation, apoptosis, migration and invasion in cSCC tumor. Furthermore, we comprehensively described the tumor microenvironment (TME) landscape and potential keratinocyte-TME crosstalk in cSCC providing theoretical basis for immunotherapy. Together, our findings provide a valuable resource for deciphering the progression from AK to cSCC and identifying potential targets for anticancer treatment of cSCC.

cancer biology↗

bioRxiv2022

The Inherited Rate Matrix algorithm for phylogenetic model selection for non-stationary Markov processes

In phylogenetic reconstruction, substitution models that assume nucleotide frequencies do not change through time are in very widespread use. DNA sequences can exhibit marked compositional difference. Such compositional heterogeneity implies sequence divergence has arisen from substitution processes that differ between the lineages. Accordingly, there has been considerable interest in exploring the non-stationary model class, which is capable of generating divergent sequence composition. These models are typically parameter rich and this richness is further compounded by the use of time-heterogeneous variants in order to capture compositional heterogeneity. This illuminates two barriers limiting the widespread application of the non-stationary model class: both the compute-time required to fit a model and the risk of model over-fitting increase with the number of parameters and the extent of time-heterogeneity. In this study, we address these issues with a novel model selection algorithm we term the Inherited Rate Matrix algorithm (hereafter IRM). This approach is based on the notion that a species inherits the substitution tendencies of its ancestor. We further present the non-stationary heterogeneous across lineages model (hereafter ns-HAL algorithm) which extends the HAL algorithm of Jayaswal et al. [2014] to the general nucleotide Markov process. The IRM algorithm substantially reduces the complexity of identifying a sufficient solution to the problem of time-heterogeneous substitution processes across lineages. We also address the issue of reducing the computing time with development of a constrained-optimisation approach for the IRM algorithm (fast-IRM). Our algorithms are implemented in Python 3. From a simulation study based on 2nd codon position genome sequences of yeast, we establish that IRM is significantly more accurate than both ns-HAL and heterogeneity in the substitution process across lineages (hereafter HAL) for close and dispersed sequences. IRM is up to 70x faster than ns-HAL while fast-IRM is around 140x faster. fast-IRM also showed a marked speed improvement over a C++ implementation of HAL. Our comparison of the accuracy of IRM with fast-IRM showed no difference with identical inferences made for all data sets. These two algorithms greatly improve the compute time for model selection of a non-stationary process, increasing the suite of problems to which this important substitution model class can be applied.

bioinformatics↗

bioRxiv2022

An in vivo avian model of human melanoma to perform rapid and robust preclinical studies

Metastatic melanoma patients carrying a BRAFV600 mutation can be treated with BRAF inhibitors (BRAFi), in combination with MEK inhibitors (MEKi), but innate and acquired resistance invariably occurs. Resistance can involve transcriptional- and epigenetic-based phenotypic adaptations, as yet unpredictable. Predicting patient response to targeted therapies is crucial to guide clinical decision. We describe here the development of a highly efficient patient-derived xenograft model adapted to patient melanoma biopsies, using the avian embryo as a host (AVI-PDX). In this in vivo paradigm, we depict a fast and reproducible tumor engraftment of patient samples within the embryonic skin, preserving key molecular and phenotypic features. We show that sensitivity and resistance to BRAFi/MEKi targeted therapies can be reliably modeled in these AVI-PDX, as well as synergies with other drugs, such as HDACi. We further provide proof-of-concept that the AVI-PDX models the diversity of responses of melanoma patients to BRAFi/MEKi, within days, hence positioning it as a valuable tool for the design of personalized medicine assays and for the evaluation of novel combination strategies.

cancer biology↗