Biology subjects

Huang, J.-F.

Publications and source records attributed to Huang, J.-F..

6 recordsLinked to original sources

bioRxiv2025

Evolution of sideways locomotion in crabs

The evolutionary change in the mode of locomotion is often a major evolutionary event, triggering diversification. Sideways locomotion is a defining feature of true crabs (Brachyura) and may have contributed to their ecological success. Yet, the evolutionary origin of this unique behavior remains unknown. Here we show that the prevalence of sideways locomotion in true crabs reflects a single evolutionary origin from a forward-moving ancestor. Our behavioral analysis of 50 live crab species indicates that crab locomotion can be broadly separated into two predominant modes, sideways and forward locomotion. The phylogenetic comparative analysis revealed a single origin of sideways locomotion, with multiple independent reversions to forward locomotion in ecologically specialized groups. The species richness data show that the lineage in which sideways locomotion originated is far more diverse than its nearest outgroups. These results are consistent with the idea that sideways locomotion acted as a key innovation contributing to the evolutionary diversification of true crabs. Such a rare but innovative behavioral trait provides a framework for understanding how locomotor modes shape evolutionary diversification in animals.

evolutionary biology↗

bioRxiv2024

Male Mice Have no Sugar-preference Behavior

Sugar-preference behavior is considered to be universally innate among humans and animals. Current research on the detection and mechanisms of sugar-preference behavior largely adopts the "two-bottle choice assay", and most experiments use male mice as the model, which has serious methodological flaws, leading to questionable conclusions. As expected, through adopting our improved experimental method, we discovered distinct sugar preferences between male and female mice: females possess an innate preference, while males do not. However, the innate sugar preference in female mice can be lost due to their long-term normal diet. Even after "training" with high-sugar food for a long time, the results still show differences between males and females. Female mice retain a significant preference for sugar, while male mice are not influenced by the training of high-sugar food and still do not evolve a sugar preference. From this, we conclude that gender determines the emergence and development of sugar preference in mice. Our results can provide researchers with a new understanding of sugar preference, which will help them fill in or even correct the gaps in the original experimental design methods to obtain more reliable conclusions.

animal behavior and cognition↗

bioRxiv2023

Predictive Systems Biology Modeling: Unraveling Host Metabolic Disruptions and Potential Drug Targets in SARS-CoV-2 and Its Variants

BackgroundHost response is critical to the onset, progression, and outcome of viral infections. Since viruses hijack the host cellular metabolism for their replications, we hypothesized that restoring host cell metabolism can efficiently reduce viral production. ResultsHere, we present a viral-host Metabolic Modeling (vhMM) method to systematically evaluate the disturbances in host metabolism in viral infection and computationally identify targets for modulation by integrating genome-wide precision metabolic modeling and cheminformatics. We applied vhMM to SARS-CoV-2 infections and identified consistent changes in host metabolism and gene and endogenous metabolite targets between the original SARS-COV-2 and different variants (Alpha, Delta, and Omicron). Among six compounds predicted for repurposing, methotrexate, cinnamaldehyde, and deferiprone were tested in vitro and effective in inhibiting viral production with IC50 less than 4uM. Further, an analysis of real-world patient data showed that cinnamon usage significantly reduced the SARS-CoV-2 infection rate with an odds ratio of 0.65 [95%CI: 0.55[~]0.75]. ConclusionsThese results demonstrated that vhMM is an efficient method for predicting targets and drugs for viral infections.

systems biology↗

bioRxiv2020

Study on β-Chitosan against the binding of SARS-CoV-2S-RBD/ACE2

SARS-CoV-2 invades human respiratory epithelial cells via an interaction between its spike RBD protein (SARS-CoV-2 S-RBD) and the host cell receptor angiotensin converting enzyme II (ACE2). Blocking this interaction provides a potent approach to preventing and controlling SARS-CoV-2 infection. In this work, the ability of {beta}-chitosan to block the binding interaction between SARS-CoV-2 S-RBD and ACE2 was investigated. The inhibitory effect of {beta}-chitosan on inflammation induced by the SARS-CoV-2 S-RBD was also studied. Native-PAGE analysis indicated that {beta}-chitosan could bind with ACE2 and the SARS-CoV-2 S-RBD and a conjugate of {beta}-chitosan and ACE2 could no longer bind with the SARS-CoV-2 S-RBD. HPLC analysis suggested that a conjugate of {beta}-chitosan and the SARS-CoV-2 S-RBD displayed high binding affinity without dissociation under high pressure (40 MPa) compared with that of {beta}-chitosan and ACE2. Furthermore, immunofluorescent staining of Vero E6 cells and lungs from hACE2 mice showed that the presence of {beta}-chitosan prevented SARS-CoV-2 S-RBD from binding to ACE2. Meanwhile, {beta}-chitosan could dramatically suppress the inflammation caused by the presence of the SARS-CoV-2 S-RBD both in vitro and vivo. Moreover, the decreased expression of ACE2 caused by {beta}-chitosan treatment was restored by addition of TAPI-1, an inhibitor of the transmembrane protease ADAM17. Our findings demonstrated that {beta}-chitosan displays an antibody-like function capable of neutralizing the SARS-CoV-2 S-RBD and effectively preventing the binding of the SARS-CoV-2 S-RBD to ACE2. Moreover, ADAM17 activation induced by {beta}-chitosan treatment can enhance the cleavage of the extracellular domain of ACE2, releasing the active ectodomain into the extracellular environment, which can prevent the binding, internalization, and degradation of ACE2 bound to the SARS-CoV-2 S-RBD and thus diminish inflammation. Our study provides an alternative avenue for preventing SARS-CoV-2 infection using {beta}-chitosan.

cell biology↗

bioRxiv2017

Anti-HIV activity prediction and enrichment identify novel human targets for Anti-HIV therapy

Human immunodeficiency virus (HIV) relies heavily on the host proteins to facilitate its entry and replication. Currently, more than 4000 human proteins are recorded to be involved in the HIV-1 life cycle. Identifying appropriate anti-HIV targets from so many host proteins is crucial to anti-HIV drug development, but a challenging work. Here we combined anti-HIV activity prediction and enrichment analysis to identify novel human targets for anti-HIV therapy. We firstly developed an accurate prediction tool named Anti-HIV-Predictor (AUC>0.96) to predict the anti-HIV activity of given compounds. Using this tool, we predicted 10488 anti-HIV compounds from ChEMBLdb. Then, based on this result and relationships of targets and compounds, we inferred 73 anti-HIV targets that enriched with anti-HIV compounds. The functional annotation and network analysis revealed that they directly or indirectly interact with 20 HIV proteins through neuropeptide signaling, GPCR signaling, cell surface signaling pathway, and so on. Nearly half of these targets overlap with the NCBI HIV dataset. However, the percentage of known therapeutic targets in these targets is significantly higher than that in the NCBI HIV dataset. After a series of feature analysis, we identified 13 novel human targets with high potential as anti-HIV targets, the inhibitors of which have experimentally confirmed anti-HIV activity. It is noteworthy that the inhibitors of REN and CALCA have better anti-HIV activity than CCR5 inhibitors. Taken together, our findings provide novel human targets for the host-oriented anti-HIV drug development and should significantly advance current anti-HIV research.

bioinformatics↗

bioRxiv2016

Efficient repositioning of approved drugs as anti-HIV agents using Anti-HIV-Predictor

Development of new, effective and affordable drugs against HIV is urgently needed. In this study, we developed a worlds first web server called Anti-HIV-Predictor (http://bsb.kiz.ac.cn:70/hivpre) for predicting anti-HIV activity of given compounds. This server is rapid and accurate (accuracy >93% and AUC > 0.958). We applied the server to screen 1835 approved drugs for anti-HIV therapy. Totally 67 drugs were predicted to have anti-HIV activity, 25 of which are anti-HIV drugs. Then we experimentally evaluated 35 predicted new anti-HIV compounds by assays of syncytia formation, p24 quantification, cytotoxicity. Finally, we repurposed 7 approved drugs (cetrorelix, dalbavancin, daunorubicin, doxorubicin, epirubicin, idarubicin and valrubicin) as new anti-HIV agents. The original indication of these drugs is involved in a variety of diseases such as female infertility and cancer. Anti-HIV-Predictor and the 7 repurposed anti-HIV agents provided here demonstrate the efficacy of this strategy for discovery of new anti-HIV agents.

bioinformatics↗