Biology subjects

Hoang, T. N.

Publications and source records attributed to Hoang, T. N..

6 recordsLinked to original sources

bioRxiv2026

FlowTransOP: Distributional Translation of Omics Signatures via Constrained Deep Flow Matching

Observations from pre-clinical models rarely generalize to human patients, leading to many failures in clinical trials. Most existing methods cannot handle domains with non-overlapping features and no paired samples. Here, we developed FlowTransOP to translate biological observations across such domains without requiring 1-to-1 feature mappings and paired data, while providing a guideline for model selection across four translational regimes. We use flow matching to align full domain distributions in a pre-aligned latent space, with a structural regularization term that keeps similar conditions proximate after transformation. FlowTransOP remains competitive with gold-standard approaches requiring paired samples, but outperforms them when pairs become scarce (<35 pairs) or when cross-domain features are only moderately correlated (r<=0.58). Overall, FlowTransOP can translate perturbations between pre-clinical models and patients when direct correspondences are unavailable, enabling reliable therapeutic inference. As a proof-of-concept, we trained a foundational mouse-human transcriptomic map on ARCHS4 and applied it to liver disease predictions.

bioinformatics↗

bioRxiv2023

Autoencoder Model for Translating Omics Signatures

The development of effective therapeutics and vaccines for human diseases requires a systematic understanding of human biology. While animal and in vitro culture models have successfully elucidated the molecular mechanisms of diseases in many studies, they yet fail to adequately recapitulate human biology as evidenced by the predominant likelihood of failure in clinical trials. To address this broadly important problem, we developed AutoTransOP, a neural network autoencoder framework to map omics profiles from designated species or cellular contexts into a global latent space, from which germane information can be mapped between different contexts. This approach performs as well or better than extant machine learning methods and can identify animal/culture-specific molecular features predictive of other contexts, without requiring homology matching. For an especially challenging test case, we successfully apply our framework to a set of inter-species vaccine serology studies, where no 1-1 mapping between human and non-human primate features exists.

bioinformatics↗

bioRxiv2022

Modulation of type I interferon responses potently inhibits SARS-CoV-2 replication and inflammation in rhesus macaques

Type-I interferons (IFN-I) are critical mediators of innate control of viral infections, but also drive recruitment of inflammatory cells to sites of infection, a key feature of severe COVID-19. Here, and for the first time, IFN-I signaling was modulated in rhesus macaques (RMs) prior to and during acute SARS-CoV-2 infection using a mutated IFN2 (IFN-modulator; IFNmod), which has previously been shown to reduce the binding and signaling of endogenous IFN-I. In SARS-CoV-2-infected RMs, IFNmod reduced both antiviral and inflammatory ISGs. Notably, IFNmod treatment resulted in a potent reduction in (i) SARS-CoV-2 viral load in Bronchoalveolar lavage (BAL), upper airways, lung, and hilar lymph nodes; (ii) inflammatory cytokines, chemokines, and CD163+MRC1-inflammatory macrophages in BAL; and (iii) expression of Siglec-1, which enhances SARS-CoV-2 infection and predicts disease severity, on circulating monocytes. In the lung, IFNmod also reduced pathogenesis and attenuated pathways of inflammasome activation and stress response during acute SARS-CoV-2 infection. This study, using an intervention targeting both IFN- and IFN-{beta} pathways, shows that excessive inflammation driven by type 1 IFN critically contributes to SARS-CoV-2 pathogenesis in RMs, and demonstrates the potential of IFNmod to limit viral replication, SARS-CoV-2 induced inflammation, and COVID-19 severity.

immunology↗

bioRxiv2021

TREM2+ and interstitial macrophages orchestrate airway inflammation in SARS-CoV-2 infection in rhesus macaques

The COVID-19 pandemic remains a global health crisis, yet, the immunopathological mechanisms driving the development of severe disease remain poorly defined. Here, we utilize a rhesus macaque (RM) model of SARS-CoV-2 infection to delineate perturbations in the innate immune system during acute infection using an integrated systems analysis. We found that SARS-CoV-2 initiated a rapid infiltration (two days post infection) of plasmacytoid dendritic cells into the lower airway, commensurate with IFNA production, natural killer cell activation, and induction of interferon-stimulated genes. At this early interval, we also observed a significant increase of blood CD14-CD16+ monocytes. To dissect the contribution of lung myeloid subsets to airway inflammation, we generated a novel compendium of RM-specific lung macrophage gene expression using a combination of sc-RNA-Seq data and bulk RNA-Seq of purified populations under steady state conditions. Using these tools, we generated a longitudinal sc-RNA-seq dataset of airway cells in SARS-CoV-2-infected RMs. We identified that SARS-CoV-2 infection elicited a rapid recruitment of two subsets of macrophages into the airway: a C206+MRC1-population resembling murine interstitial macrophages, and a TREM2+ population consistent with CCR2+ infiltrating monocytes, into the alveolar space. These subsets were the predominant source of inflammatory cytokines, accounting for ~75% of IL6 and TNF production, and >90% of IL10 production, whereas the contribution of CD206+MRC+ alveolar macrophages was significantly lower. Treatment of SARS-CoV-2 infected RMs with baricitinib (Olumiant(R)), a novel JAK1/2 inhibitor that recently received Emergency Use Authorization for the treatment of hospitalized COVID-19 patients, was remarkably effective in eliminating the influx of infiltrating, non-alveolar macrophages in the alveolar space, with a concomitant reduction of inflammatory cytokines. This study has delineated the major subsets of lung macrophages driving inflammatory and anti-inflammatory cytokine production within the alveolar space during SARS-CoV-2 infection. One sentence summaryMulti-omic analyses of hyperacute SARS-CoV-2 infection in rhesus macaques identified two population of infiltrating macrophages, as the primary orchestrators of inflammation in the lower airway that can be successfully treated with baricitinib

microbiology↗

bioRxiv2020

Baricitinib treatment resolves lower airway inflammation and neutrophil recruitment in SARS-CoV-2-infected rhesus macaques

Effective therapeutics aimed at mitigating COVID-19 symptoms are urgently needed. SARS-CoV-2 induced hypercytokinemia and systemic inflammation are associated with disease severity. Baricitinib, a clinically approved JAK1/2 inhibitor with potent anti-inflammatory properties is currently being investigated in COVID-19 human clinical trials. Recent reports suggest that baricitinib may also have antiviral activity in limiting viral endocytosis. Here, we investigated the immunologic and virologic efficacy of baricitinib in a rhesus macaque model of SARS-CoV-2 infection. Viral shedding measured from nasal and throat swabs, bronchoalveolar lavages and tissues was not reduced with baricitinib. Type I IFN antiviral responses and SARS-CoV-2 specific T cell responses remained similar between the two groups. Importantly, however, animals treated with baricitinib showed reduced immune activation, decreased infiltration of neutrophils into the lung, reduced NETosis activity, and more limited lung pathology. Moreover, baricitinib treated animals had a rapid and remarkably potent suppression of alveolar macrophage derived production of cytokines and chemokines responsible for inflammation and neutrophil recruitment. These data support a beneficial role for, and elucidate the immunological mechanisms underlying, the use of baricitinib as a frontline treatment for severe inflammation induced by SARS-CoV-2 infection.

immunology↗

bioRxiv2017

MULTILOCUS SEQUENCE TYPING REVEALS A UNIQUE CO-DOMINANT POPULATION STRUCTURE OF CRYPTOCOCCUS NEOFORMANS VAR. GRUBII IN VIETNAM

Cryptococcosis is amongst the most important invasive fungal infections globally, with cryptococcal meningitis causing an estimated 180,000 deaths each year in HIV infected patients alone. Patients with other forms of immunosuppression are also at risk, and disease is increasingly recognized in apparently immunocompetent individuals. Cryptococcus neoformans var. grubii (serotype A, molecular type VNI) has a global distribution and is responsible for the majority of cases. Here, we used the consensus ISHAM Multilocus Sequence Typing (MLST) for C. neoformans to define the population structure of clinical isolates of Cryptococcus neoformans var. grubii from Vietnam (n=136) and Laos (n=81). We placed these isolates into the global context using published MLST data from 8 other countries (total N = 669). We observed a phylo-geographical relationship in which Laos was similar to its Southeast Asian neighbor Thailand in being dominated (83%) by Sequence Type (ST) 4 and its Single Locus Variant ST6. On the other hand, Vietnam was uniquely intermediate between Southeast Asia and East Asia having both ST4/ST6 (35%) and ST5 (48%) which causes the majority of cases in East Asia. Analysis of genetic distance (Fst) between different populations of Cryptococcus neoformans var. grubii supported the intermediate nature of the population from Vietnam. A strong association between ST5 and infection in apparently immunocompetent, HIV-uninfected patients was observed in Vietnam (OR: 7.97, [95%CI: 3.18-19.97], p < 0.0001). Our study emphasizes that Vietnam, with its intermediate Cryptococcus neoformans var. grubii population structure, provides the strongest epidemiological evidence of the relationship between ST5 and infection of HIV-uninfected patients. Human population genetic distances within the region suggest these differences in CNVG population across Southeast Asia are driven by ecological factors rather than host factors.\n\nAuthor summaryCryptococcus neoformans is a yeast that causes meningitis in people, usually with damaged immune systems. There are >180,000 deaths in HIV-infected patients each year, most occurring where there are the highest HIV/AIDS disease burdens. Vietnam and Laos have contributed significantly to clinical trials aiming to improve the treatment of cryptococcal meningitis, but the relationship of isolates from these countries to the global population is not yet described. Here, we address this knowledge gap by using Multilocus Sequence Typing to study the population of Cryptococcus neoformans var. grubii (CNVG) in Laos and Vietnam, with the specific aim of incorporating these populations into the wider global context. We found that, in most countries, a single lineage (family) of strains was responsible for most disease. The Vietnamese CNVG population was unusual in that 2 main lineages circulated at the same time. The Vietnamese CNVG population occupies a middle ground between Thailand/Laos in the west and China in the east. The differences in population structure moving from West to East are probably due to ecological differences. Disease in HIV uninfected patients was almost always due to members of a single family of strains (ST5).

molecular biology↗