Plasma and urine proteomics and gut microbiota analysis reveal potential factors affecting COVID-19 vaccination response

The efficacy of COVID-19 vaccination relies on the induction of neutralizing antibodies, which can vary among vaccine recipients. In this study, we investigated the potential factors affecting the neutralizing antibody response by combining plasma and urine proteomics and gut microbiota analysis. We found that activation of the LXR/FXR pathway in plasma was associated with the production of ACE2-RBD-inhibiting antibodies, while urine proteins related to complement system, acute phase response signaling, LXR/FXR, and STAT3 pathways were correlated with neutralizing antibody production. Moreover, we observed a correlation between the gut microbiota and plasma and urine proteins, as well as the vaccination response. Based on the above data, we built a predictive model for vaccination response (AUC = 0.85). Our study provides insights into characteristic plasma and urine proteins and gut microbiota associated with the ACE2-RBD-inhibiting antibodies, which could benefit our understanding of the host response to COVID-19 vaccination.

Deep molecular learning of transcriptional control of a synthetic CRE enhancer and its variants

Massively parallel reporter assay measures transcriptional activities of various cis-regulatory modules (CRMs) in a single experiment. We developed a thermodynamic computational model framework that calculates quantitative levels of gene expression directly from regulatory DNA sequences. Using the framework, we investigated the molecular mechanisms of cis-regulatory mutations of a synthetic enhancer that cause abnormal gene expression. We found that, in a human cell line, competitive binding between family transcription factors (TFs) with slightly different binding preferences significantly increases the accuracy of recapitulating the transcriptional effects of thousands of single- or multi-mutations. We also discovered that even if various harmful mutations occurred in an activator binding site, CRM could stably maintain or even increase gene expression through a certain form of competitive binding between family TFs. These findings enhance understanding the effect of SNPs and indels on CRMs and would help building robust custom-designed CRMs for biologics production and gene therapy.

Patient-derived organoids as personalized avatars and a potential immunotherapy model in cervical cancer

Cervical cancer remains a significant health issue in developing countries. However, finding a preclinical model that accurately reproduces tumor characteristics is challenging. Therefore, we established a patient-derived organoids (PDOs) biobank containing 67 cases of heterogeneous cervical cancer that mimic the histopathological and genomic characteristics of parental tumors. The in vitro response of the organoids indicated their ability to capture the radiological heterogeneity of the patients. To model individual responses to adoptive T cell therapy (ACT), we expanded tumor-infiltrating lymphocytes (TILs) ex vivo and co-cultured them with paired organoids. The PDOs-TILs co-culture system demonstrates clear responses that correspond to established immunotherapy efficiency markers like the proportion of CTLs. This study supports the potential of the PDOs platform to guide treatment in prospective interventional trials in cervical cancer.

A computational model of the DNA damage-induced IKK/ NF-κB pathway reveals a critical dependence on irradiation dose and PARP-1

The activation of IKK/NF-κB by genotoxic stress is a crucial process in the DNA damage response. Due to the anti-apoptotic impact of NF-κB, it can affect cell-fate decisions upon DNA damage and therefore interfere with tumor therapy-induced cell death. Here, we developed a dynamical model describing IKK/NF-κB signaling that faithfully reproduces quantitative time course data and enables a detailed analysis of pathway regulation. The approach elucidates a pathway topology with two hubs, where the first integrates signals from two DNA damage sensors and the second forms a coherent feedforward loop. The analyses reveal a critical role of the sensor protein PARP-1 in the pathway regulation. Introducing a method for calculating the impact of changes in individual components on pathway activity in a time-resolved manner, we show how irradiation dose influences pathway activation. Our results give a mechanistic understanding relevant for the interpretation of experimental and clinical studies.

A spatially structured mathematical model of the gut microbiome reveals factors that increase community stability

Given the importance of gut microbial communities for human health, we may want to ensure their stability in terms of species composition and function. Here, we built a mathematical model of a simplified gut composed of two connected patches where species and metabolites can flow from an upstream patch, allowing upstream species to affect downstream species' growth. First, we found that communities in our model are more stable if they assemble through species invasion over time compared to combining a set of species from the start. Second, downstream communities are more stable when species invade the downstream patch less frequently than the upstream patch. Finally, upstream species that have positive effects on downstream species can further increase downstream community stability. Despite it being quite abstract, our model may inform future research on designing more stable microbial communities or increasing the stability of existing ones.

Integrative analysis of single-cell RNA-seq and ATAC-seq reveals heterogeneity of induced pluripotent stem cell-derived hepatic organoids

To gain deeper insights into transcriptomes and epigenomes of organoids, liver organoids from two states (expandable and more differentiated) were subjected to single-cell RNA-seq (scRNA-seq) and single-cell ATAC-seq (scATAC-seq) analyses. Mitochondrial gene expression was higher in differentiated than in non-differentiated hepatocytes, with ATAC-seq peaks increasing near the mitochondrial control region. Differentiation of liver organoids resulted in the expression of transcription factors that act as enhancers and repressors. In addition, epigenetic mechanisms regulating the expression of alpha-fetoprotein (AFP) and albumin (ALB) differed in liver organoids and adult liver. Knockdown of PDX1, an essential transcription factor for pancreas development, led to the hepatic maturation of liver organoids through regulation of AFP and ALB expression. This integrative analysis of the transcriptomes and epigenomes of liver organoids at the single-cell level may contribute to a better understanding of the regulatory networks during liver development and the further development of mature in vitro human liver models.

A metabolic regulatory network for the Caenorhabditis elegans intestine

Metabolic perturbations can affect gene expression, for instance to rewire metabolism. While numerous efforts have measured gene expression in response to individual metabolic perturbations, methods that determine all metabolic perturbations that affect the expression for a given gene or set of genes have not been available. Here, we use a gene-centered approach to derive a first-pass metabolic regulatory network for Caenorhabditis elegans by performing RNAi of more than 1,400 metabolic genes with a set of 19 promoter reporter strains that express a fluorescent protein in the animal's intestine. We find that metabolic perturbations generally increase promoter activity, which contrasts with transcription factor (TF) RNAi, which tends to repress promoter activity. We identify several TFs that modulate promoter activity in response to perturbations of the electron transport chain and explore complex genetic interactions among metabolic pathways. This work provides a blueprint for a systems-level understanding of how metabolism affects gene expression.

Exploring the metabolic landscape of pancreatic ductal adenocarcinoma cells using genome-scale metabolic modeling

Pancreatic ductal adenocarcinoma (PDAC) is a major research focus because of its poor therapy response and dismal prognosis. PDAC cells adapt their metabolism to the surrounding environment, often relying on diverse nutrient sources. Because traditional experimental techniques appear exhaustive to find a viable therapeutic strategy, a highly curated and omics-informed PDAC genome-scale metabolic model was reconstructed using patient-specific transcriptomics data. From the model-predictions, several new metabolic functions were explored as potential therapeutic targets in addition to the known metabolic hallmarks of PDAC. Significant downregulation in the peroxisomal beta oxidation pathway, flux modulation in the carnitine shuttle system, and upregulation in the reactive oxygen species detoxification pathway reactions were observed. These unique metabolic traits of PDAC were correlated with potential drug combinations targeting genes with poor prognosis in PDAC. Overall, this study provides a better understanding of the metabolic vulnerabilities in PDAC and will lead to novel effective therapeutic strategies.

The cost of bacterial predation via type VI secretion system leads to predator extinction under environmental stress

As a common gut pathogen, Campylobacter jejuni (C. jejuni) harbors the Type VI Secretion System (T6SS) that injects toxic effectors into neighboring cells, modulating microbial competitions in the harsh gut environment. Using bile salt as a natural stressor and T6SS-positive C. jejuni as a predator, we show that T6SS activity could entail a cost during bacterial predation under environmental stress. Our data suggest bile salt influx and subsequent DNA damage due to the prey-driven activation of the T6SS. We further combined experiments and mathematical modeling to explore how the stress-induced “predation cost” determines ecological outcomes. Consistent with a population-dynamics model, we found predator extinction above a critical bile salt concentration and prey-predator coexistence below this level. Moreover, we utilized the predation cost as an effective strategy facilitating host defense against C. jejuni infection. Together, we elucidate how predator dominance versus extinction emerges from the interplay between environmental stress and the T6SS machinery.

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Campylobacter jejuni uses Type VI secretion system (T6SS) to kill prey bacteria

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Under bile salt stress, activated T6SS may promote bile salt uptake and DNA damage

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T6SS-dependent predation by C. jejuni thus entails a “predation cost” under stress

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The predation cost leads to predator extinction and host defense against C. jejuni

Logical and experimental modeling of cytokine and eicosanoid signaling in psoriatic keratinocytes

Psoriasis is a chronic skin disease, in which immune cells and keratinocytes keep each other in a state of inflammation. It is believed that phospholipase A2 (PLA2)-dependent eicosanoid release plays a key role in this. T-helper (Th) 1-derived cytokines are established activators of phospholipases in keratinocytes, whereas Th17-derived cytokines have largely unknown effects. Logical model simulations describing the function of cytokine and eicosanoid signaling networks combined with experimental data suggest that Th17 cytokines stimulate proinflammatory cytokine expression in psoriatic keratinocytes via activation of cPLA2α-Prostaglandin E2-EP4 signaling, which could be suppressed using the anti-psoriatic calcipotriol. cPLA2α inhibition and calcipotriol distinctly regulate expression of key psoriatic genes, possibly offering therapeutic advantage when applied together. Model simulations additionally suggest EP4 and protein kinase cAMP-activated catalytic subunit alpha as drug targets that may restore a normal phenotype. Our work illustrates how the study of complex diseases can benefit from an integrated systems approach.

A stochastic model of homeostasis: The roles of noise and nuclear positioning in deciding cell fate

We study a population-based cellular model that starts from a single stem cell that divides stochastically to give rise to either daughter stem cells or differentiated daughter cells. There are three main components in the model: nucleus position, the underlying gene-regulatory network, and stochastic segregation of transcription factors in the daughter cells. The proportion of self-renewal and differentiated cell lines as a function of the nucleus position which in turn decides the plane of cleavage is studied. Both nuclear position and noise play an important role in determining the stem cell genealogies. We have observed both long and short genealogies in model simulation, and these compare well with experimental results from neuroblast and B-cell division. Symmetric divisions are observed in apical nuclei, while asymmetric division occurs when the nucleus is toward the base. In this model, the number of clones decreases over time, although the average clone size increases.