Biology subjects

Mi, H.

Publications and source records attributed to Mi, H..

5 recordsLinked to original sources

bioRxiv2018

The permeabilized SecY protein-translocation channel can serve as a nonspecific sugar transporter

As the initial step in carbohydrate catabolism in cells, the substrate-specific transporters via active transport and facilitated diffusion play a decisive role in passage of sugars through the plasma membrane into the cytoplasm. The SecY complex (SecYEG) in bacteria forms a membrane channel responsible for protein translocation. This work demonstrates that weakening the sealability of the SecY channel allowed free diffusion of sugars, including glucose, fructose, mannose, xylose, arabinose, and lactose, into the engineered cells, facilitating its rapid growth on a wide spectrum of monosaccharides and bypassing/reducing stereospecificity, transport saturation, competitive inhibition, and carbon catabolite repression (CCR), which are usually encountered with the specific sugar transporters. The SecY channel is structurally conserved in prokaryotes, thus it may be engineered to serve as a unique and universal transporter for bacteria to passage sugars as demonstrated in Escherichia coli and Clostridium acetobutylicum.

bioengineering↗

bioRxiv2018

Resolving challenges in quantitative modeling of microbial community dynamics

Microbial communities can perform biochemical activities that monocultures cannot. Controlling communities requires an understanding of community dynamics. Here, we mathematically predict the growth rate of an engineered community consisting of two S. cerevisiae strains, each releasing a metabolite required and consumed by the partner. Initial model parameters were based on strain phenotypes measured in batch mono-cultures with zero or excess metabolite, and failed to quantitatively predict experimental results. To resolve model-experiment discrepancy, we chemically identified the correct exchanged metabolites, but this did not improve model performance. We then re-measured strain phenotypes in chemostats mimicking the metabolite-limited community environments, while mitigating or incorporating effects of rapid evolution. Almost all phenotypes we measured varied significantly with the metabolite environment. Once we used parameters measured in community-like chemostat environments, prediction agreed with experimental results. In summary, using a simplified community, we uncovered, and devised means to resolve, modeling challenges that are likely general.

microbiology↗

bioRxiv2018

Intercellular signaling network underlies biological time across multiple temporal scales

MotivationCellular, physiological and molecular processes must be organized and regulated across multiple time domains throughout the lifespan of an organism. The technological revolution in molecular biology has led to the identification of numerous genes implicated in the regulation of diverse temporal biological processes. However, it is natural to question whether there is an underlying regulatory network governing multiple timescales simultaneously.\n\nResultsUsing queries of relevant databases and literature searches, a single dense multiscale temporal regulatory network was identified involving core sets of genes that regulate circadian, cell cycle, and aging processes. The network was highly enriched for genes involved in signal transduction (P = 1.82e-82), with p53 and its regulators such as p300 and CREB binding protein forming key hubs, but also for genes involved in metabolism (P = 6.07e-127) and cellular response to stress (P = 1.56e-93). These results suggest an intertwined molecular signaling network that affects biological time across multiple temporal scales in response to environmental stimuli and available resources.\n\nContactjoshua.millstein@usc.edu\n\nSupplementary informationSupplementary data are available online.

systems biology↗

bioRxiv2018

BDQC: a general-purpose analytics tool for domain-blind validation of Big Data

Translational biomedical research is generating exponentially more data: thousands of whole-genome sequences (WGS) are now available; brain data are doubling every two years. Analyses of Big Data, including imaging, genomic, phenotypic, and clinical data, present qualitatively new challenges as well as opportunities. Among the challenges is a proliferation in ways analyses can fail, due largely to the increasing length and complexity of processing pipelines. Anomalies in input data, runtime resource exhaustion or node failure in a distributed computation can all cause pipeline hiccups that are not necessarily obvious in the output. Flaws that can taint results may persist undetected in complex pipelines, a danger amplified by the fact that research is often concurrent with the development of the software on which it depends. On the positive side, the huge sample sizes increase statistical power, which in turn can shed new insight and motivate innovative analytic approaches. We have developed a framework for Big Data Quality Control (BDQC) including an extensible set of heuristic and statistical analyses that identify deviations in data without regard to its meaning (domain-blind analyses). BDQC takes advantage of large sample sizes to classify the samples, estimate distributions and identify outliers. Such outliers may be symptoms of technology failure (e.g., truncated output of one step of a pipeline for a single genome) or may reveal unsuspected \" signal\" in the data (e.g., evidence of aneuploidy in a genome). We have applied the framework to validate real-world WGS analysis pipelines. BDQC successfully identified data outliers representing various failure classes, including genome analyses missing a whole chromosome or part thereof, hidden among thousands of intermediary output files. These failures could then be resolved by reanalyzing the affected samples. BDQC both identified hidden flaws as well as yielded new insights into the data. BDQC is designed to complement quality software development practices. There are multiple benefits from the application of BDQC at all pipeline stages. By verifying input correctness, it can help avoid expensive computations on flawed data. Analysis of intermediary and final results facilitates recovery from aberrant termination of processes. All these computationally inexpensive verifications reduce cryptic analytical artifacts that could seriously preclude clinical-grade genome interpretation. BDQC is available at https://github.com/ini-bdds/bdqc.

bioinformatics↗

bioRxiv2017

A cortical pathway modulates sensory input into the olfactory striatum

Sensory cortices process stimuli in manners essential for perception. The piriform primary olfactory cortex (PCX) extends dense association fibers into the ventral striatums olfactory tubercle (OT), yet the function of this cortico-striatal pathway is unknown. We optically stimulated channelrhodopsin-transduced PCX glutamatergic neurons or their association fibers while recording OT neural activity in mice performing an olfactory task. Activation of PCX neurons or their association fibers within the OT controlled the firing of some OT neurons and bidirectionally modulated odor coding dependent upon the neurons intrinsic odor responsivity. Further, patch clamp recordings and retroviral tracing from D1 and D2 dopamine receptor-expressing OT medium spiny neurons revealed this input can be monosynaptic and that both cell types receive most of their input from a specific spatial zone localized within the ventro-caudal PCX. These results demonstrate that the PCX functionally accesses the direct and indirect pathways of the basal ganglia within the OT.

neuroscience↗