Biology subjects

Tang, H.

Publications and source records attributed to Tang, H..

At least 91 records · Page 5Linked to original sources

bioRxiv2024

Detecting phenotype-specific tumor microenvironment by merging bulk and single cell expression data to spatial transcriptomics

In addressing the limitations of current multimodal analysis methods that largely ignore phenotypic data, leading to a lack of biological interpretability at the phenotypic level, we developed the Single-Cell and Tissue Phenotype prediction (SCTP), a deep-learning-based multimodal fusion framework. SCTP can simultaneously detect phenotype-specific cells and characterize the tumor microenvironment of pathological tissue by integrating essential information from the bulk sample phenotype, the composition of individual cells, and the spatial distribution of cells. Upon evaluating SCTPs efficiency and robustness against traditional analytical methods, we developed a specialized model, SCTP-CRC, tailored for colorectal cancer (CRC). This model integrates RNA-seq, scRNA-seq, and spatial transcriptomic data to offer a better understanding of CRC. SCTP-CRC has proven effective in accurately identifying tumor-associated cells and clusters and continuously defines boundary regions as well as the spatial organization of the entire tumor microenvironment. This enables a detailed depiction of cellular communication networks, capturing the dynamic shifts that occur during tumor progression. Furthermore, SCTP-CRC extends to the identification of abnormal sub-regions in the early state of CRC and uncovers potential early-warning signature genes such as MMP2, IGKC, and PIGR. These biomarkers are not only important in recognizing the onset of CRC but may also play a crucial role in differentiating between CRC-derived liver metastases and primary liver tumors. SCTP stands as a transformative framework, offering a deeper understanding of the tumor microenvironment through its ability to quantitatively characterize cancers fundamental traits and dissect the intricate molecular and cellular interactions at play. This comprehensive insight supports the early diagnosis and enables personalized treatment strategies, marking a significant stride toward improving patient outcomes and tailoring therapies to individual disease profiles.

bioinformatics↗

bioRxiv2024

Integrated multi-omics analysis of Klebsiella pneumoniae revealed the discrepancy in flavonoid effect against strain growth between Rutin and Luteolin

The emergence of drug resistant pathogenic bacteria is increasingly challenging conventional antibiotics. Plant derived flavonoids are always considered as potential alternatives to antibiotics due to their antimicrobial properties. However, the molecular mechanisms by which flavonoids inhibit pathogenic microorganisms growth are not fully understood. In order to better understand the inhibitory mechanism of flavonoids, two flavonoids were used to incubate Klebsiella pneumoniae ATCC700603. After incubation for 4 hours, both the metabolomic and transcriptomic analysis were performed. In present study, 5,483 genes and 882 metabolites were measured. Compared to wild control, the Rutin and Luteolin induced 507 and 374 differentially expressed genes (DEGs), respectively. However, the number of differential abundant metabolites (DAMs) were the same. The correlation between DEGs and DAMs were studied. The top 10 correlated DEGs and DAMs were identified in each comparative groups. Our results showed that, compared to Luteolin, Rutin induced the accumulation of metabolites and suppressed genes expression. Our results provided an explanation for the disparate effects of two flavonoids and demonstrated the inhibitory mechanism of Rutin on strain growth.

bioinformatics↗

bioRxiv2024

Spike Neural Network of Motor Cortex Model for Arm Reaching Controlling

Motor cortex modeling is crucial for understanding movement planning and execution. While interconnected recurrent neural networks have successfully described the dynamics of neural population activity, most existing methods utilize continuous signal-based neural networks, which do not reflect the biological spike neural signal. To address this limitation, we propose a recurrent spike neural network to simulate motor cortical activity during an arm-reaching task. Specifically, our model is built upon integrate-and-fire spiking neurons with conductance-based synapses. We carefully designed the interconnections of neurons with two different firing time scales - "fast" and "slow" neurons. Experimental results demonstrate the effectiveness of our method, with the models neuronal activity in good agreement with monkeys motor cortex data at both single-cell and population levels. Quantitative analysis reveals a correlation coefficient 0.89 between the models and real data. These results suggest the possibility of multiple timescales in motor cortical control.

neuroscience↗

bioRxiv2024

Recruitment of the m6A/Am demethylase FTO to target RNAs by the telomeric zinc finger protein ZBTB48

N6-methyladenosine (m6A), the most abundant internal modification on eukaryotic mRNA, and N6, 2'-O-dimethyladenosine (m6Am), are epitranscriptomic marks that function in multiple aspects of posttranscriptional regulation. Fat mass and obesity-associated protein (FTO) can remove both m6A and m6Am; however, little is known about how FTO achieves its substrate selectivity. Here, we demonstrate that ZBTB48, a C2H2-zinc finger protein that functions in telomere maintenance, associates with FTO and binds both mRNA and the telomere-associated regulatory RNA TERRA to regulate the functional interactions of FTO with target transcripts. Specifically, depletion of ZBTB48 affects targeting of FTO to sites of m6A/m6Am modification, changes cellular m6A/m6Am levels and, consequently, alters decay rates of target RNAs. ZBTB48 ablation also accelerates growth of HCT-116 colorectal cancer cells and modulates FTO- dependent regulation of Metastasis-associated protein 1 (MTA1) transcripts by controlling the binding to MTA1 mRNA of the m6A reader IGF2BP2. Our findings thus uncover a previously unknown mechanism of posttranscriptional regulation in which ZBTB48 co-ordinates RNA- binding of the m6A/m6Am demethylase FTO to control expression of its target RNAs.

molecular biology↗

bioRxiv2023

Epigenetic disruption of the RARγ complex impairs its function to bookmark AR enhancer interactions required for enzalutamide sensitivity in prostate cancer

The current study in prostate cancer (PCa) focused on the genomic mechanisms at the cross-roads of pro-differentiation signals and the emergence of lineage plasticity. We explored an understudied cistromic mechanism involving RAR{gamma}s ability to govern AR cistrome-transcriptome relationships, including those associated with more aggressive PCa features. The RAR{gamma} complex in PCa cell models was enriched for canonical cofactors, as well as proteins involved in RNA processing and bookmarking. Identifying the repertoire of miR-96 bound and regulated gene targets, including those recognition elements marked by m6A, revealed their significant enrichment in the RAR{gamma} complex. RAR{gamma} significantly enhanced the AR cistrome, particularly in active enhancers and super-enhancers, and overlapped with the binding of bookmarking factors. Furthermore, RAR{gamma} expression led to nucleosome-free chromatin enriched with H3K27ac, and significantly enhanced the AR cistrome in G2/M cells. RAR{gamma} functions also antagonized the transcriptional actions of the lineage master regulator ONECUT2. Similarly, gene programs regulated by either miR-96 or antagonized by RAR{gamma} were enriched in alternative lineages and more aggressive PCa phenotypes. Together these findings reveal an under-investigated role for RAR{gamma}, modulated by miR-96, to bookmark enhancer sites during mitosis. These sites are required by the AR to promote transcriptional competence, and emphasize luminal differentiation, while antagonizing ONECUT2.

cancer biology↗

bioRxiv2023

Protein domain embeddings for fast and accurate similarity search

Recently developed protein language models have enabled a variety of applications with the protein contextual embeddings they produce. Per-protein representations (each protein is represented as a vector of fixed dimension) can be derived via averaging the embeddings of individual residues, or applying matrix transformation techniques such as the discrete cosine transformation to matrices of residue embeddings. Such protein-level embeddings have been applied to enable fast searches of similar proteins, however limitations have been found; for example, PROST is good at detecting global homologs but not local homologs, and knnProtT5 excels for proteins of single domains but not multi-domain proteins. Here we propose a novel approach that first segments proteins into domains (or subdomains) and then applies the discrete cosine transformation to the vectorized embeddings of residues in each domain to infer domain-level contextual vectors. Our approach, called DCTdomain, utilizes predicted contact maps from ESM-2 for domain segmentation, which is formulated as a domain segmentation problem and can be solved using a recursive cut algorithm (RecCut in short) in quadratic time to the protein length; for comparison, an existing approach for domain segmentation uses a cubic-time algorithm. We showed such domain-level contextual vectors (termed as DCT fingerprints) enable fast and accurate detection of similarity between proteins that share global similarities but with undefined extended regions between shared domains, and those that only share local similarities.

bioinformatics↗

bioRxiv2023

Computational mechanisms underlying motivation to earn symbolic reinforcers

Reinforcement learning (RL) is a theoretical framework that describes how agents learn to select options that maximize rewards and minimize punishments over time. We often make choices, however, to obtain symbolic reinforcers (e.g. money, points) that can later be exchanged for primary reinforcers (e.g. food, drink). Although symbolic reinforcers are motivating, little is understood about the neural or computational mechanisms underlying the motivation to earn them. In the present study, we examined how monkeys learn to make choices that maximize fluid rewards through reinforcement with tokens. The question addressed here is how the value of a state, which is a function of multiple task features (e.g. current number of accumulated tokens, choice options, task epoch, trials since last delivery of primary reinforcer, etc.), drives value and affects motivation. We constructed a Markov decision process model that computes the value of task states given task features to capture the motivational state of the animal. Fixation times, choice reaction times, and abort frequency were all significantly related to values of task states during the tokens task (n=5 monkeys). Furthermore, the model makes predictions for how neural responses could change on a moment-by-moment basis relative to changes in state value. Together, this task and model allow us to capture learning and behavior related to symbolic reinforcement. Significance statementSymbolic reinforcers, like money and points, play a critical role in our lives. Like rewards, symbolic reinforcers can be motivating and can even lead to compulsive behaviors like gambling addiction. However, we lack an understanding of how symbolic reinforcement can drive fluctuations in motivation. Here we investigated the effect of symbolic reinforcers on behaviors related to motivation during a token reinforcement learning task, using a novel reinforcement learning model and data from five monkeys. Our findings suggest that the value of a task state can affect willingness to initiate a trial, speed to choose, and persistence to complete a trial. Our model makes testable predictions for within trial fluctuations of neural activity related to values of task states.

neuroscience↗

bioRxiv2023

Voxel-wise regression without intensity normalizationprovides better sensitivity when identifying injuryregions after stroke in FDG-PET images

BackgroundIn the analysis of brain fluorodeoxyglucose positron emission tomography (FDG-PET), intensity normalization is a necessary step to reduce inter-subject variability. However, the choice of an appropriate normalization method in stroke studies remains unclear, leading to inconsistent findings in the literature. Materials and methodsHere, we propose a regression-based and single-subject-based model for analyzing FDG-PET images without intensity normalization. Two independent data sets were collected before and after middle cerebral artery occlusion (MCAO), with one comprising 120 rats and the other comprising 96 rats. After data preprocessing, voxel intensities in the same region and hemisphere were paired before and after the MCAO scan. A linear regression model was applied to the paired data, and the coefficient of determination was calculated to measure the linearity. The results between the ipsilateral and contralateral hemispheres were compared, and significant regions were defined as those having reduced linearity. Our method was compared with existing intensity normalization methods and validated using the triphenyl tetrazolium chloride (TTC) staining data. ResultsThe proposed method detected more injury areas compared to existing approaches, as confirmed by the ground truth provided by TTC. The area under the curve (AUC) of the average receiver operating characteristic (ROC) curves using our method reached 0.84, whereas the AUCs using existing methods ranged from 0.77 [~] 0.79. The average false positive rate (FPR) and true positive rate (TPR) of the individual analysis results using our method (FPR = 0.06, TPR = 0.56) were better than the group-wise analysis results using t-tests (FPR = 0.10, TPR = 0.51). The identified injury regions were consistent in the two independent data sets. Some of them were confirmed by other publications. ConclusionsThe proposed method offers a new quantitative approach to analyzing FDG-PET images. The calculation does not involve intensity normalization and can be applied to a single subject. The method yields more sensitive results than existing intensity normalization methods.

neuroscience↗

bioRxiv2023

Preclinical evaluation of the efficacy and safety of AAV1-hOTOF in mice and non-human primates

Pathogenic mutations in the OTOF gene cause autosomal recessive hearing loss 9 (DFNB9), one of the most common forms of auditory neuropathy. There is no biological treatment for DFNB9. Here, we designed an OTOF gene therapy agent by dual AAV1 carrying human OTOF coding sequences with the expression driven by the hair cell-specific promoter Myo15, AAV1-hOTOF. To develop a clinical application of AAV1-hOTOF gene therapy, we evaluated its efficacy and safety in animal models by pharmacodynamics, behavior, and histopathology. AAV1-hOTOF inner ear delivery significantly improved hearing in Otof -/- mice without affecting normal hearing in wild-type mice. AAV1 was predominately distributed to the cochlea although it was detected in other organs such as the central nervous system and the liver, and no obvious toxic effects of AAV1-hOTOF were observed in mice. To further evaluate the safety of Myo15 promoter-driven AAV1-transgene, AAV1-GFP was delivered into the inner ear of Macaca fascicularis via the round window membrane. AAV1-GFP transduced 60-94% of the inner hair cells along the cochlear turns. AAV1-GFP was detected in isolated organs and no significant adverse effects were detected. These results suggest that AAV1-hOTOF is well tolerated and effective in animals, providing critical support for its clinical translation.

genetics↗

bioRxiv2023

The heterogeneity and effect of diabetes and hypertension on spectral characteristics of vasomotion

Vasomotion refers to the spontaneous oscillation of blood vessels within a frequency range of 0.01 to 1.6 Hz. Various disease states, including hypertension and diabetes, have been associated with alterations in vasomotion at the finger, indicating potential impairment of skin microcirculation. Due to the non-linear nature of human vasculature, the modification of vasomotion may vary across different locations for different diseases. In this study, Laser Doppler Flowmetry was used to measure blood flow motion at acupoints LU8, LU5, SP6, and PC3 among 49 participants with or without diabetes and/or hypertension. Fast Fourier Transformation was used to analyze noise type while Hilbert-Huang Transformation and wavelet analysis were applied to assess Signal Noise Ratio (SNR) results. Statistical analysis revealed that different acupoints exhibit distinct spectral characteristics of vasomotion not only among healthy individuals but also among patients with diabetes and hypertension. The results showed strong heterogeneity of vasomotion among blood vessels, indicating that the vasomotion measured at a certain point may not reflect the real status of microcirculation.

bioengineering↗

bioRxiv2023

A Novel Humanized Immune Stroma PDX Cancer Model for Therapeutic Studies

Standard preclinical human tumor models lack a human tumor stroma. However, as stroma contributes to therapeutic resistance, the lack of human stroma may make current models less stringent for testing new therapies. To address this, using patient-derived tumor cells, patient derived cancer-associated mesenchymal stem/progenitor cells, and human endothelial cells, we created a Human Stroma-Patient Derived Xenograft (HS-PDX) tumor model. HS-PDX, compared to the standard PDX model, demonstrate greater resistance to targeted therapy and chemotherapy, and better reflect patient response to therapy. Furthermore, HS-PDX can be grown in mice with humanized bone marrow to create humanized immune stroma patient-derived xenograft (HIS-PDX) models. The HIS-PDX model contains human connective tissues, vascular and immune cell infiltrates. RNA sequencing analysis demonstrated a 94-96% correlation with primary human tumor. Using this model, we demonstrate the impact of human tumor stroma on response to CAR-T cell therapy and immune checkpoint inhibitor therapy. We show an immunosuppressive role for human tumor stroma and that this model can be used to identify immunotherapeutic combinations to overcome stromally mediated immunosuppression. Combined, our data confirm a critical role for human stoma in therapeutic response and indicate that HIS-PDX can be an important tool for preclinical drug testing. Statement of SignificanceWe developed a tumor model with human stromal, vascular, and immune cells. This model mirrors patient response to chemotherapy, targeted therapy, and immunotherapy, and can be used to study therapy resistance.

cancer biology↗

bioRxiv2023

Roles of Lipopolysaccharide Glycosyltransferases in Maintenance of Helicobacter pylori Morphology, Cell Wall Permeability, and Antimicobial Susceptibilities

Helicobacter pylori unique lipopolysaccharide structure is essential in maintaining the cell envelop integrity and renders the bacterium natural resistance to cationic antimicrobial peptides (CAMPs). Our group has recently elucidated the complete set of LPS glycosyltransferase genes in H. pylori reference strain G27. Here, with a series of 8 systematically constructed LPS glycosyltransferase gene mutants (G27{Delta}HP1578, G27{Delta}HP1283, G27{Delta}HP0159, G27{Delta}HP0479, G27{Delta}HP0102, G27{Delta}wecA, G27{Delta}HP1284 and G27{Delta}HP1191), we investigated the roles of H. pylori LPS glycosyltransferases in maintenance of cell morphology, cell wall permeability, and antimicrobial susceptibilities. We demonstrated that deletion of these LPS glycosyltransferase genes did not interfere with bacterial cell wall permeability, but resulted in significant morphological changes (coccoid, coiled "c"-shape, and irregular shapes) after 48 h growth as compared to the rod-like cell shape of the wild-type strain. Moreover, as compared with the wild-type, none of the LPS mutants had altered susceptibility against clarithromycin, levofloxacin, amoxicillin, tetracycline, and metronidazole. However, the deletion of the conserved LPS glycosyltransferases, especially the O-antigen initiating enzyme WecA displayed a dramatic increase in susceptibility to the CAMP polymyxin B and rifampicin. Taken together, our findings suggest that the LPS glycosyltransferases play critical roles in the maintenance of the typical spiral morphology of H. pylori, as well as resistance to CAMPs and rifampicin. The LPS glycosyltransferases could be promising targets for developing novel anti-H. pylori drugs. ImportanceH. pylori typical helical morphology, cell wall integrity, as well as resistance to cationic CAMPs and antimicrobials are significant factors for its long-term colonization and persistent infection in human gastric mucosa. Our results show that each of the 8 LPS glycosyltransferase genes (HP1578, HP1283, HP0159, HP0479, HP0102, wecA, HP1284 and HP1191) deletion did not interfere with bacterial cell wall permeability, but resulted in significant loss of H. pylori typical helical shape. Furthermore, deletion of the conserved LPS glycosyltransferases, especially the O-antigen initiating enzyme WecA displayed a dramatic increase in susceptibility to the CAMP polymyxin B and rifampicin. Taken together, we believe that the LPS glycosyltransferases are good targets for developing novel anti-H. pylori drugs.

microbiology↗

bioRxiv2023

3DMolMS: Prediction of Tandem Mass Spectra from Three Dimensional Molecular Conformations

MotivationTandem mass spectrometry is an essential technology for characterizing chemical compounds at high sensitivity and throughput, and is commonly adopted in many fields. However, computational methods for automated compound identification from their MS/MS spectra are still limited, especially for novel compounds that have not been previously characterized. In recent years, in silico methods were proposed to predict the MS/MS spectra of compounds, which can then be used to expand the reference spectral libraries for compound identification. However, these methods did not consider the compounds three-dimensional (3D) conformations, and thus neglected critical structural information. ResultsWe present the 3D Molecular Network for Mass Spectra Prediction (3DMolMS), a deep neural network model to predict the MS/MS spectra of compounds from their 3D conformations. We evaluated the model on the experimental spectra collected in several spectral libraries. The results showed that 3DMolMS predicted the spectra with the average cosine similarity of 0.687 and 0.475 with the experimental MS/MS spectra acquired in positive and negative ion modes, respectively. Furthermore, 3DMolMS model can be generalized to the prediction of MS/MS spectra acquired by different labs on different instruments through minor fine-tuning on a small set of spectra. Finally, we demonstrate that the molecular representation learned by 3DMolMS from MS/MS spectra prediction can be adapted to enhance the prediction of chemical properties such as the elution time (ET) in the liquid chromatography and the Collisional Cross Section (CCS) measured by ion mobility spectrometry (IMS), both of which are often used to improve compound identification. Contacthatang@indiana.edu Supplementary informationThe codes of 3DMolMS is available at https://github.com/JosieHong/3DMolMS and the web service is at https://spectrumprediction.gnps2.org.

bioinformatics↗

bioRxiv2023

A promising QTL QSns.sau-MC-3D.1 likely superior to WAPO1 for wheat spikelet number per spike shows no adverse effects on yield-related traits

Spikelet number per spike (SNS) is one of the crucial factors determining wheat yield. Thus, improving our understanding of the genes that regulate SNS could help develop higher-yielding wheat varieties. A genetic linkage map constructed using the GenoBaits Wheat 16K Panel and the 660K SNP array contained 5991 polymorphic SNP markers spanning 2813.26 cM. A total of twelve QTL for SNS were detected in the recombinant inbred line (RIL) population msf x Chuannong 16 (MC), and two of them, i.e., QSns.sau-MC-3D.1 and QSns.sau-MC-7A, were stably expressed. QSns.sau-MC-3D.1 had high LOD values ranging from 4.99 to 11.06 and explained 9.71-16.75% of the phenotypic variation. Comparison of QSns.sau-MC-3D.1 with previously reported SNS QTL suggested that it is likely a novel one. A kompetitive allele-specific PCR (KASP) marker, KASP-10, tightly linked to QSns.sau-MC-3D.1 was developed to successfully validate its effect in three segregated populations and a natural population. Genetic analysis indicated that WHEAT ORTHOLOG OFAPO1 (WAPO1) was a candidate gene for QSns.sau-MC-7A. The combined additive effect of QSns.sau-MC-3D.1 and WAP01 had a great additive effect increasing SNS by 7.10%. In addition, our results suggested that SNS is not affected by 1BL/1RS translocations in the MC RIL population. Correlation analysis between two major QTL and other agronomic traits showed that QSns.sau-MC-3D.1 was likely independent of these agronomic traits. However, the H2 haplotype of WAPO1 may affect effective tiller number and plant height. This indicated that the breeding potential of QSns.sau-MC-3D.1 is better than that of WAPO1. The geographical distribution of QSns.nsau-MC-3D.1 showed that QSns.sau-MC-3D.1 positive allele frequency was dominant in most wheat-producing regions of China and it has been positively selected among modern cultivars released in China since the 1940s. Two genes, TraesCS3D03G0222600 and TraesCS3D03G0216800, associated with SNS development were predicted in the physical interval of QSns.sau-MC-3D.1. qRT-PCR results of the two genes showed that only the expression level of TraesCS3D03G0216800 was significantly different between msf and CN16. These results enrich our understanding of the genetic basis of wheat SNS and will be useful for fine mapping and cloning of genes underlying QSns.sau-MC-3D.1, and provide a basis for marker-assisted selection breeding. Author summaryIn this study, we identified two major QTL (QSns.sau-MC-3D.1 and QSns.sau-MC-7A) in a RIL population. WAPO1 was demonstrated to be the candidate gene for QSns.sau-MC-7A. QSns.sau-MC-3D.1 was a novel and stably expressed QTL, and further confirmed in different genetic backgrounds. Our results further demonstrate that QSns.sau-MC-3D.1 has better breeding potential because of its no adverse effect on other agronomic traits than WAPO1, and it has been positively selected during Chinese breeding programs since the 1940s. Taken together, the identification of QSns.sau-MC-3D.1 offers a promising resource to further increase wheat yields.

genetics↗

bioRxiv2023

Omicron Spike Protein Is Vulnerable to Reduction

SARS-CoV-2 virus spike (S) protein is an envelope protein responsible for binding to the ACE2 receptor, driving subsequent entry into host cells. The existence of multiple disulfide bonds in the S protein makes it potentially susceptible to reductive cleavage. Using a tri-part split luciferase-based binding assay, we evaluated the impacts of chemical reduction on S proteins from different virus variants and found that those from the Omicron family are highly vulnerable to reduction. Through manipulation of different Omicron mutations, we found that alterations in the receptor binding module (RBM) are the major determinants of this vulnerability. Specifically we discovered that Omicron mutations facilitate the cleavage of C480-C488 and C379-C432 disulfides, which consequently impairs binding activity and protein stability. The vulnerability of Omicron S proteins suggests a mechanism that can be harnessed to treat specific SARS-CoV-2 strains.

biochemistry↗

bioRxiv2022

Resting-State fMRI reveals Longitudinal Alterations in Brain Network Connectivity in a Mouse Model of Huntington's Disease

Huntingtons disease is an autosomal, dominantly inherited neurodegenerative disease caused by an expansion of the CAG repeats in exon 1 of the huntingtin gene. Neuronal degeneration and dysfunction that precedes regional atrophy result in the impairment of striatal and cortical circuits that affect the brains large-scale network functionality. However, the evolution of these disease-driven, large-scale connectivity alterations is still poorly understood. Here we used resting-state fMRI to investigate functional connectivity changes in a mouse model of Huntingtons disease in several relevant brain networks and how they are affected at different ages that follow a disease-like phenotypic progression. Towards this, we used the heterozygous (HET) form of the zQ175DN Huntingtons disease mouse model that recapitulates aspects of human disease pathology. Seed- and Region-based analyses were performed at different ages, on 3-, 6-, 10-, and 12-month-old HET and age-matched wild-type mice. Our results demonstrate decreased connectivity starting at 6 months of age, most prominently in regions such as the retrosplenial and cingulate cortices, pertaining to the default mode-like network and auditory and visual cortices, part of the associative cortical network. At 12 months, we observe a shift towards decreased connectivity in regions such as the somatosensory cortices, pertaining to the lateral cortical network, and the caudate putamen, a constituent of the subcortical network. Moreover, we assessed the impact of distinct Huntingtons Disease-like pathology of the zQ175DN HET mice on age-dependent connectivity between different brain regions and networks where we demonstrate that connectivity strength follows a nonlinear, inverted U-shape pattern, a well-known phenomenon of development and normal aging. Conversely, the neuropathologically driven alteration of connectivity, especially in the default mode and associative cortical networks, showed diminished age-dependent evolution of functional connectivity. These findings reveal that in this Huntingtons disease model, altered connectivity starts with cortical network aberrations which precede striatal connectivity changes, which appear only at a later age. Taken together, these results suggest that the age-dependent cortical network dysfunction seen in rodents could represent a relevant pathological process in Huntingtons disease progression.

neuroscience↗

bioRxiv2022

MSP1 encodes an essential RNA-binding PPR factor required for nad1 maturation and complex I biogenesis in Arabidopsis mitochondria

SummaryMitochondria are semi-autonomous organelles that serve as hubs for aerobic energy metabolism. The biogenesis of the respiratory (OXPHOS) system relies on nuclear-encoded factors, which regulate the transcription, processing and translation of mitochondrial (mt)RNAs. These include proteins of primordial origin, as well as eukaryotic-type RNA-binding families recruited from the host genomes to function in mitogenome expression. Pentatricopeptide repeat (PPR) proteins constitute a major gene-family in angiosperms that is pivotal in many aspects of mtRNA metabolism, such as editing, splicing or stability. Here, we report the analysis of MITOCHONDRIA STABILITY/PROCESSING PPR FACTOR1 (MSP1, At4g20090), a canonical mitochondria-localized PPR protein that is necessary for mitochondrial biogenesis and embryo-development. Functional complementation confirmed that the phenotypes result from a disruption of the MSP1 gene. As a loss-of-function allele of Arabidopsis MSP1 leads to seed abortion, we employed an embryo-rescue method for the molecular characterization of msp1 mutants. Our data show that msp1 embryo-development fails to proceed beyond the heart-torpedo transition stage as a consequence of a severe nad1 pre-RNA processing-defect, resulting in the loss of respiratory complex I (CI) activity. The maturation of nad1 involves the processing of three RNA-fragments, nad1.1, nad1.2 and nad1.3. Based on biochemical analyses and the mtRNA profiles in wild-type and msp1 plants, we concluded that through its association with a specific site in nad1.1, MSP1 facilitates the generation of its 3-terminus and stabilizes it -a prerequisite for nad1 exons a-b splicing. Our data substantiate the importance of mtRNA metabolism for the biogenesis of the respiratory machinery during early-plant development.

plant biology↗

bioRxiv2022

Longitudinal investigation of changes in resting-state co-activation patterns and their predictive ability in the zQ175 DN mouse model of Huntington's disease

Huntingtons disease (HD) is a neurodegenerative disorder caused by expanded ([≥]40) glutamine-encoding CAG repeats in the huntingtin gene, which leads to dysfunction and death of predominantly striatal and cortical neurons. While the genetic profile and behavioural signs of the disease are better known, changes in the functional architecture of the brain, especially before the behavioural symptoms become apparent, are not fully and consistently characterized. In this study, we sought markers at pre, early and late manifest states of phenotypic progression in the heterozygous (HET) zQ175 delta-neo (DN) mouse model, using resting-state functional magnetic resonance imaging (RS-fMRI). This mouse model shows molecular, cellular and circuitry alterations that resemble those seen in HD in humans. Specifically, we investigated, longitudinally, changes in co-activation patterns (CAPs) that are the transient states of brain activity constituting the resting-state networks (RSNs). Most robust changes in the temporal properties of CAPs occurred at the late manifest state; the durations of two anti-correlated CAPs, characterized by simultaneous co-activation of default-mode like network (DMLN) and co-deactivation of lateral-cortical network (LCN) and vice-versa, were reduced in the zQ175 DN HET animals compared to the wild-type mice. Changes in the spatial properties, measured in terms of activation levels of different brain regions, during CAPs were found at all three states and became progressively more pronounced at the manifest states. We then assessed the cross-validated predictive power of CAP metrics to distinguish HET animals from controls. Spatial properties of CAPs performed significantly better than the chance level at all three states with 80% classification accuracy at the early and late manifest states.

neuroscience↗