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"Clark, Ryan"
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Design of synthetic human gut microbiome assembly and butyrate production
The capability to design microbiomes with predictable functions would enable new technologies for applications in health, agriculture, and bioprocessing. Towards this goal, we develop a model-guided approach to design synthetic human gut microbiomes for production of the health-relevant metabolite butyrate. Our data-driven model quantifies microbial interactions impacting growth and butyrate production separately, providing key insights into ecological mechanisms driving butyrate production. We use our model to explore a vast community design space using a design-test-learn cycle to identify high butyrate-producing communities. Our model can accurately predict community assembly and butyrate production across a wide range of species richness. Guided by the model, we identify constraints on butyrate production by high species richness and key molecular factors driving butyrate production, including hydrogen sulfide, environmental pH, and resource competition. In sum, our model-guided approach provides a flexible and generalizable framework for understanding and accurately predicting community assembly and metabolic functions.
Microbiomes designed with predictable functions could enable broad applications in health, agriculture and bioprocessing. Here the authors use a model-guided approach to design diverse synthetic human gut communities for production of the health-relevant metabolite butyrate.
Journal Article
Review of cone beam computed tomography based online adaptive radiotherapy: current trend and future direction
Adaptive radiotherapy (ART) was introduced in the late 1990s to improve the accuracy and efficiency of therapy and minimize radiation-induced toxicities. ART combines multiple tools for imaging, assessing the need for adaptation, treatment planning, quality assurance, and has been utilized to monitor inter- or intra-fraction anatomical variations of the target and organs-at-risk (OARs). Ethos™ (Varian Medical Systems, Palo Alto, CA), a cone beam computed tomography (CBCT) based radiotherapy treatment system that uses artificial intelligence (AI) and machine learning to perform ART, was introduced in 2020. Since then, numerous studies have been done to examine the potential benefits of Ethos™ CBCT-guided ART compared to non-adaptive radiotherapy. This review will explore the current trends of Ethos™, including improved CBCT image quality, a feasible clinical workflow, daily automated contouring and treatment planning, and motion management. Nevertheless, evidence of clinical improvements with the use of Ethos™ are limited and is currently under investigation via clinical trials.
Journal Article
Atlas of the 2016 elections
The 2016 election was one of the most dramatic upsets in US history. Explaining the surprising Trump victory, the leading scholars trace the entire gamut of the election. Illustrated with over 100 meticulous full-color maps, the atlas will be an essential reference and a fascinating resource for pundits, voters, campaign staffs, and political junkies.
Book
Recurrent neural networks enable design of multifunctional synthetic human gut microbiome dynamics
Predicting the dynamics and functions of microbiomes constructed from the bottom-up is a key challenge in exploiting them to our benefit. Current models based on ecological theory fail to capture complex community behaviors due to higher order interactions, do not scale well with increasing complexity and in considering multiple functions. We develop and apply a long short-term memory (LSTM) framework to advance our understanding of community assembly and health-relevant metabolite production using a synthetic human gut community. A mainstay of recurrent neural networks, the LSTM learns a high dimensional data-driven non-linear dynamical system model. We show that the LSTM model can outperform the widely used generalized Lotka-Volterra model based on ecological theory. We build methods to decipher microbe-microbe and microbe-metabolite interactions from an otherwise black-box model. These methods highlight that Actinobacteria, Firmicutes and Proteobacteria are significant drivers of metabolite production whereas Bacteroides shape community dynamics. We use the LSTM model to navigate a large multidimensional functional landscape to design communities with unique health-relevant metabolite profiles and temporal behaviors. In sum, the accuracy of the LSTM model can be exploited for experimental planning and to guide the design of synthetic microbiomes with target dynamic functions.
Journal Article
Negative interactions determine Clostridioides difficile growth in synthetic human gut communities
Understanding the principles of colonization resistance of the gut microbiome to the pathogen
Clostridioides difficile
will enable the design of defined bacterial therapeutics. We investigate the ecological principles of community resistance to
C. difficile
using a synthetic human gut microbiome. Using a dynamic computational model, we demonstrate that
C. difficile
receives the largest number and magnitude of incoming negative interactions. Our results show that
C. difficile
is in a unique class of species that display a strong negative dependence between growth and species richness. We identify molecular mechanisms of inhibition including acidification of the environment and competition over resources. We demonstrate that
Clostridium hiranonis
strongly inhibits
C. difficile
partially via resource competition. Increasing the initial density of
C. difficile
can increase its abundance in the assembled community, but community context determines the maximum achievable
C. difficile
abundance. Our work suggests that the
C. difficile
inhibitory potential of defined bacterial therapeutics can be optimized by designing communities featuring a combination of mechanisms including species richness, environment acidification, and resource competition.
SYNOPSIS
A combination of bottom‐up community assembly and computational modeling reveals determinants of
Clostridioides difficile
growth in synthetic human gut communities.
The inferred interspecies interaction network reveals that
C. difficile
receives the largest number and magnitude of incoming negative interactions.
The richness of a community, environmental acidification by a community, propagule pressure and resource competition are major determinants of
C. difficile
growth.
Clostridium hiranonis
consumes resources utilized by
C. difficile
and inhibits
C. difficile
growth.
Graphical Abstract
A combination of bottom‐up community assembly and computational modeling reveals determinants of
Clostridioides difficile
growth in synthetic human gut communities.
Journal Article
Simulation of RSO Images for Space Situation Awareness (SSA) Using Parallel Processing
With the rapid increase in resident space objects (RSO), there is a growing demand for their identification and characterization to advance space simulation awareness (SSA) programs. Various AI-based technologies are proposed and demonstrated around the world to effectively and efficiently identify RSOs from ground and space-based observations; however, there remains a challenge in AI training due to the lack of labeled datasets for accurate RSO detection. In this paper, we present an overview of the starfield simulator to generate a realistic representation of images from space-borne imagers. In particular, we focus on low-resolution images such as those taken with a commercial-grade star tracker that contains various RSO in starfield images. The accuracy and computational efficiency of the simulator are compared to the commercial simulator, namely STK-EOIR to demonstrate the performance of the simulator. In comparing over 1000 images from the Fast Auroral Imager (FAI) onboard CASSIOPE satellite, the current simulator generates both stars and RSOs with approximately the same accuracy (compared to the real images) as STK-EOIR and, an order of magnitude faster in computational speed by leveraging parallel processing methodologies.
Journal Article
Dynamic alterations in decoy VEGF receptor-1 stability regulate angiogenesis
Blood vessel expansion is driven by sprouting angiogenesis of endothelial cells, and is essential for development, wound healing and disease. Membrane-localized vascular endothelial growth factor receptor-1 (mVEGFR1) is an endothelial cell-intrinsic decoy receptor that negatively modulates blood vessel morphogenesis. Here we show that dynamic regulation of mVEGFR1 stability and turnover in blood vessels impacts angiogenesis. mVEGFR1 is highly stable and constitutively internalizes from the plasma membrane. Post-translational palmitoylation of mVEGFR1 is a binary stabilization switch, and ligand engagement leads to depalmitoylation and lysosomal degradation. Trafficking of palmitoylation enzymes via Rab27a regulates mVEGFR1 stability, as reduced levels of Rab27a impaired palmitoylation of mVEGFR1, decreased its stability, and elevated blood vessel sprouting and
in vivo
angiogenesis. These findings identify a regulatory axis affecting blood vessel morphogenesis that highlights exquisite post-translational regulation of mVEGFR1 in its role as a molecular rheostat.
Membrane-bound mVEGFR1 is a decoy VEGF-A receptor that regulates VEGF-A signalling amplitude. Boucher
et al
. show that Rab27a-regulated palmitoylation of mVEGFR1 redirects the receptor from a stable, constitutively recycling mode to a degradative route that removes ligands from the system.
Journal Article
Intercellular communication and conjugation are mediated by ESX secretion systems in mycobacteria
Communal bacterial processes require intercellular communication mediated by secretion systems to coordinate appropriate molecular responses. Intercellular communication has not been described previously in mycobacteria. Here we show that the ESX secretion-system family member ESX-4 is essential for conjugal recipient activity in Mycobacterium smegmatis. Transcription of esx4 genes in the recipient requires coculture with a donor strain and a functional ESX-1 apparatus in the recipient. Conversely, mutation of the donor ESX-1 apparatus amplifies the esx4 transcriptional response in the recipient. The effect of ESX-1 on esx4 transcription correlates with conjugal DNA transfer efficiencies. Our data show that intercellular communication via ESX-1 controls the expression of its evolutionary progenitor, ESX-4, to promote conjugation between mycobacteria.
Journal Article