Biology subjects

Shen, D.

Publications and source records attributed to Shen, D..

48 records · Page 3Linked to original sources

bioRxiv2020

Involuntary orienting and conflict resolution during auditory attention: The role of ventral and dorsal streams

Selective attention to sound object features such as pitch and location is associated with enhanced brain activity in ventral and dorsal streams, respectively. We examined the role of these pathways in involuntary orienting and conflict resolution using functional magnetic resonance imaging (fMRI). Participants were presented with two tones that may share, or not, the same non-spatial (frequency) or spatial (location) auditory features. In separate blocks of trials, participants were asked to attend to sound frequency or sound location and ignore the change in the task-irrelevant feature. In both attend-frequency and attend-location tasks, response times were slower when the task-irrelevant feature changed than when it stayed the same (involuntary orienting). This behavioural cost coincided with enhanced activity in the prefrontal cortex and superior temporal gyrus (STG). Conflict resolution was examined by comparing situations where the change in stimulus features was congruent (both features changed) and incongruent (only one feature changed). Participants were slower and less accurate for incongruent than congruent sound features. This congruency effect was associated with enhanced activity in the prefrontal cortex, and was greater in the right STG and medial frontal cortex during the attend-location than during the attend-frequency task. Together, these findings do not support a strict division of labour into ventral and dorsal streams, but rather suggest interactions between these pathways in situations involving changes in task-irrelevant sound feature and conflict resolution. These findings also validate the Test of Attention in Listening task by revealing distinct neural correlates for involuntary orienting and conflict resolution.

neuroscience↗

bioRxiv2019

Interpretable Deep Temporal Structure Learning Model for Early Detection of Alzheimer's Disease

In Alzheimers research, Mild Cognitive Impairment (MCI) is an important intermediate stage between normal aging and Alzheimers disease. How to distinguish MCI samples that finally convert to AD from those do not is an essential problem in the prevention and diagnosis of Alzheimers. Traditional methods use various classification models to distinguish MCI converters from non-converters, while the performance is usually limited by the small number of available data. Moreover, previous methods only use the data at baseline time for training but ignore the longitudinal information at other time points along the disease progression. To tackle with these problems, we propose a novel deep learning framework that uncovers the temporal correlation structure of the longitudinal neuroimaing data in the disease progression. In the meantime, we formulate our new deep learning model in an interpretable style such that it provides insights on the important features Alzheimers research. We conduct extensive experiments on the ADNI cohort and outperform the related methods with significant margin.

neuroscience↗

bioRxiv2019

Prediction and Characterization of RXLR Effectors in Pythium Species

Being widely existed in oomycetes, the RXLR effector features conserved RXLR-dEER motifs in its N terminal. Every known Phytophthora or Hyaloperonospora pathogen harbors hundreds of RXLRs. In Pythium species, however, none of the RXLR effectors has been characterized yet. Here, we developed a stringent method for de novo identification of RXLRs and characterized 359 putative RXLR effectors from nine tested Pythium species. Phylogenetic analysis revealed a single superfamily formed by all oomycetous RXLRs, suggesting they descent from a common ancestor. RXLR effectors from Pythium and Phytophthora species exhibited similar sequence features, protein structures and genome locations. In particular, the mosquito biological agent P. guiyangense contains a significantly larger RXLR repertoire than the other eight Pythium species examined, which may result from gene duplication and genome rearrangement events as indicated by synteny analysis. Expression pattern analysis of RXLR-encoding genes in the plant pathogen P. ultimum detected transcripts from the vast majority of predicted RXLRs with some of them being induced at infection stages. One such RXLRs showed necrosis-inducing activity. Furthermore, all predicted RXLRs were cloned from two biocontrol agents P. oligandrum and P. periplocum. Three of them were found to encode effectors inducing defense response in Nicotiana benthamiana. Taken together, our findings represent the first complete synopsis of Pythium RXLR effectors, which provides critical clues on their evolutionary patterns as well as the mechanisms of their interactions with diverse hosts. Author summaryPathogens from the Pythium genus are widespread across multiple ecological niches. Most of them are soilborne plant pathogens whereas others cause infectious diseases in mammals. Some Pythium species can be used as biocontrol agents for plant diseases or mosquito management. Despite that phylogenetically close oomycete pathogens secrete RXLR effectors to enable infection, no RXLR protein was previously characterized in any Pythium species. Here we developed a stringent method to predict Pythium RXLR effectors and compared them with known RXLRs from other species. All oomycetous RXLRs form a huge superfamily, which indicates they may share a common ancestor. Our sequence analysis results suggest that the expansion of RXLR repertoire results from gene duplication and genome recombination events. We further demonstrated that most predicted Pythium RXLRs can be transcribed and some of them encode effectors exhibiting pathogenic or defense-inducing activities. This work expands our understanding of RXLR evolution in oomycetes in general, and provides novel insights into the molecular interactions between Pythium pathogens and their diverse hosts.

microbiology↗

bioRxiv2019

Large-scale transgenic Drosophila resource collections for loss- and gain-of-function studies

The Transgenic RNAi Project (TRiP), a Drosophila functional genomics platform at Harvard Medical School, was initiated in 2008 to generate and distribute a genome-scale collection of RNAi fly stocks. To date, the TRiP has generated >15,000 RNAi fly stocks. As this covers most Drosophila genes, we have largely transitioned to development of new resources based on CRISPR technology. Here, we present an update on our libraries of publicly available RNAi and CRISPR fly stocks, and focus on the TRiP-CRISPR overexpression (TRiP-OE) and TRiP-CRISPR knockout (TRiP-KO) collections. TRiP-OE stocks express sgRNAs targeting upstream of a gene transcription start site. Gene activation is triggered by co-expression of catalytically dead Cas9 (dCas9) fused to an activator domain, either VP64-p65-Rta (VPR) or Synergistic Activation Mediator (SAM). TRiP-KO stocks express one or two sgRNAs targeting the coding sequence of a gene or genes, allowing for generation of indels in both germline and somatic tissue. To date, we have generated more than 5,000 CRISPR-OE or -KO stocks for the community. These resources provide versatile, transformative tools for gene activation, gene repression, and genome engineering.

genetics↗

bioRxiv2019

Promotion of hyperthermic-induced rDNA hypercondensation in Saccharomyces cerevisiae

Ribosome biogenesis is tightly regulated through stress-sensing pathways that impact genome stability, aging and senescence. In Saccharomyces cerevisiae, ribosomal RNAs are transcribed from rDNA located on the right arm of chromosome XII. Numerous studies reveal that rDNA decondenses into a puff-like structure during interphase and condenses into a tight loop-like structure during mitosis. Intriguingly, a novel and additional mechanism of increased mitotic rDNA compaction (termed hypercondensation) was recently discovered that occurs in response to temperature stress (hyperthermic-induced) and is rapidly reversible. Here, we report that neither changes in condensin nor cohesin binding dynamics appear to play a critical role in hyperthermic-induced rDNA hypercondensation - differentiating this architectural state from normal mitotic condensation (requiring cohesins and condensins) and the premature condensation (requiring condensins) that occurs during interphase in response to nutrient starvation. A candidate genetic approach revealed that deletion of either Hsp82 or Hsc82 (Hsp90 heat shock paralogs) result in significantly reduced hyperthermic-induced rDNA hypercondensation. Intriguingly, Hsp inhibitors do not impact rDNA hypercondensation. In combination, these findings suggest that Hsp90 either stabilizes client proteins, which are sensitive to very transient thermic challenges, or directly promotes rDNA hypercondensation during preanaphase. Our findings further reveal that the high mobility group protein Hmo1 is a negative regulator of mitotic rDNA condensation, distinct from its role in promoting premature-condensation of rDNA during interphase upon nutrient starvation.

cell biology↗

bioRxiv2019

Development of Dynamic Functional Architecture during Early Infancy

Understanding the moment-to-moment dynamics of functional connectivity (FC) in the human brain during early development is crucial for uncovering neuro-mechanisms of the emerging complex cognitive functions and behaviors. Instead of calculating FC in a static perspective, we leveraged a longitudinal resting-state functional magnetic resonances imaging dataset from fifty-one typically developing infants and, for the first time, thoroughly investigated how the temporal variability of the FC architecture develops at the global (entire brain), meso- (functional system) and local (brain region) levels in the first two years of age. Our results revealed that, in such a pivotal stage, 1) the whole-brain FC dynamics is linearly increased; 2) the high-order functional systems display increased FC dynamics for both within- and between-network connections, while the primary systems show the opposite trajectories; 3) many frontal regions have increasing FC dynamics despite large heterogeneity in developmental trajectories and velocities. All these findings indicate that the brain is gradually reconfigured towards a more flexible, dynamic, and adaptive system with globally increasing but locally heterogeneous trajectories in the first two postnatal years, explaining why infants have emerging and rapidly developing high-order cognitive functions and complex behaviors.

neuroscience↗

bioRxiv2019

Bacterial fucosidase enables the production of Bombay red blood cells

We present a method to produce H antigen-deficient red blood cells (RBCs) for transfusion to individuals with anti-H antibodies. A fucosidase from bacteria was heterologously expressed efficiently in E. coli and has been demonstrated to completely remove H antigens on the surface of human RBCs in a facile conversion process. The approach we describe here holds promise for making H-deficient RBCs available for a rare population beyond ABO types.

molecular biology↗

bioRxiv2019

Towards a Better Estimation of Functional Brain Network for Mild Cognitive Impairment Identification: A Transfer Learning View

Mild cognitive impairment (MCI) is an intermediate stage of brain cognitive decline, associated with increasing risk of developing Alzheimers disease (AD). It is believed that early treatment of MCI could slow down the progression of AD, and functional brain network (FBN) could provide potential imaging biomarkers for MCI diagnosis and response to treatment. However, there are still some challenges to estimate a \"good\" FBN, particularly due to the poor quality and limited quantity of functional magnetic resonance imaging (fMRI) data from the target domain (i.e., MCI study). Inspired by the idea of transfer learning, we attempt to transfer information in high-quality data from source domain (e.g., human connectome project in this paper) into the target domain towards a better FBN estimation, and propose a novel method, namely NERTL (Network Estimation via Regularized Transfer Learning). Specifically, we first construct a high-quality network \"template\" based on the source data, and then use the template to guide or constrain the target of FBN estimation by a weighted l1-norm regularizer. Finally, we conduct experiments to identify subjects with MCI from normal controls (NCs) based on the estimated FBNs. Despite its simplicity, our proposed method is more effective than the baseline methods in modeling discriminative FBNs, as demonstrated by the superior MCI classification accuracy of 82.4% and the area under curve (AUC) of 0.910.

neuroscience↗

bioRxiv2019

Afferent-efferent connectivity between auditory brainstem and cortex accounts for poorer speech-in-noise comprehension in older adults

Age-related hearing loss leads to poorer speech comprehension, particularly in noise. Speech-in-noise (SIN) deficits among the elderly could result from weaker neural activity within, or poorer signal transmission between brainstem and auditory cortices. By recording neuroelectric responses from brainstem (BS) and primary auditory cortex (PAC), we show that beyond simply attenuating neural activity, hearing loss in older adults compromises the transmission of speech information between subcortical and cortical hubs of the auditory system. The strength of afferent BS[->]PAC neural signaling (but not the reverse efferent flow; PAC[->]BS) varied with mild declines in hearing acuity and this \"bottom-up\" functional connectivity robustly predicted older adults SIN perception. Our neuroimaging findings underscore the importance of brain connectivity, particularly afferent neural communication, in understanding the biological basis of age-related hearing deficits in real-world listening environments.

neuroscience↗

bioRxiv2018

Nitrate inhibition of nodule formation in Medicago truncatula is mediated by ACC SYNTHASE 10

Legumes form a mutualistic endosymbiosis with nitrogen-fixing rhizobia. These rhizobia are housed intracellularly in specialised lateral root organs, called nodules. Initiation of these nodules is triggered by bacterial derived signalling molecules, lipochitooligosaccharides (LCO). The process of nitrogen fixation is highly energy-demanding and therefore nodule initiation is tightly regulated. Nitrate is a potent inhibitor of nodulation. However, the precise mechanisms by which nitrate inhibits nodulation is poorly understood. Here, we demonstrate that in Medicago truncatula nitrate interferes with the transcriptional regulation of the ethylene biosynthesis gene ACC SYNTHASE 10. ACSs commit the rate limiting step in ethylene biosynthesis and in M. truncatula ACS10 is highly expressed in the zone of the root where nodulation occurs. Our results show that a reduction in ACS10 expression in response to LCO exposure correlates with the ability to form nodules. In addition, RNAi-mediated knockdown of ACS10 confers nodulation ability under otherwise inhibitory nitrate conditions. This discovery sheds new light on how ethylene is involved in the inhibition of nodulation by nitrate, bringing us one step closer to understanding how plants regulate their susceptibility towards rhizobia.

plant biology↗

bioRxiv2017

Functional Brain Network Estimation with Time Series Self-scrubbing

Functional brain network (FBN) has been becoming an increasingly important measurement for exploring the cerebral working mechanism and mining informative biomarkers for assisting diagnosis of some neurodegenerative disorders. Despite its potential performance in discovering the valuable patterns hidden in the brains, the estimated FBNs are often heavily influenced by the quality of the observed data (e.g., BOLD signal series). In practice, a preprocessing pipeline is usually employed for improving the data quality prior to the FBN estimation; but, even so, some data points in the time series are still not clean enough, possibly including original artifacts (e.g., micro head motion), non-resting functional disturbing (e.g., mind-wandering), and new \"noises\" caused by the preprocessing pipeline per se. Therefore, not all data points in the time series can contribute to the subsequent FBN estimation. To address this issue, in this paper, we propose a novel FBN estimation method by introducing a latent variable as an indicator of the data quality, and develop an alternating optimization algorithm for scrubbing the data and estimating FBN simultaneously in a single framework. As a result, we can obtain more accurate FBNs with the self-scrubbing data. To illustrate the effectiveness of the proposed method, we conduct experiments on two publicly available datasets to identify mild cognitive impairment (MCI) patients from normal control (NC) subjects based on the estimated FBNs. Experimental results show that the proposed FBN modelling method can achieve higher classification accuracy, significantly outperforming the baseline methods.

neuroscience↗

bioRxiv2017

Parallel loss of symbiosis genes in relatives of nitrogen-fixing non-legume Parasponia

Rhizobium nitrogen-fixing nodules are a well-known trait of legumes, but nodules also occur in other plant lineages either with rhizobium or the actinomycete Frankia as microsymbiont. The widely accepted hypothesis is that nodulation evolved independently multiple times, with only a few losses. However, insight in the evolutionary trajectory of nodulation is lacking. We conducted comparative studies using Parasponia (Cannabaceae), the only non-legume able to establish nitrogen fixing nodules with rhizobium. This revealed that Parasponia and legumes utilize a large set of orthologous symbiosis genes. Comparing genomes of Parasponia and its non-nodulating relative Trema did not reveal specific gene duplications that could explain a recent gain of nodulation in Parasponia. Rather, Trema and other non-nodulating species in the Order Rosales show evidence of pseudogenization or loss of key symbiosis genes. This demonstrates that these species have lost the potential to nodulate. This finding challenges a long-standing hypothesis on evolution of nitrogen-fixing symbioses, and has profound implications for translational approaches aimed at engineering nitrogen-fixing nodules in crop plants.

plant biology↗