Biology subjects

Choi, B.

Publications and source records attributed to Choi, B..

29 records · Page 2Linked to original sources

bioRxiv2021

Hierarchical Bayesian models of transcriptional and translational regulation processes with delays

MotivationSimultaneous recordings of gene network dynamics across large populations have revealed that cell characteristics vary considerably even in clonal lines. Inferring the variability of parameters that determine gene dynamics is key to understanding cellular behavior. However, this is complicated by the fact that the outcomes and effects of many reactions are not observable directly. Unobserved reactions can be replaced with time delays to reduce model dimensionality and simplify inference. However, the resulting models are non-Markovian, and require the development of new inference techniques. ResultsWe propose a non-Markovian, hierarchical Bayesian inference framework for quantifying the variability of cellular processes within and across cells in a population. We illustrate our approach using a delayed birth-death process. In general, a distributed delay model, rather than a popular fixed delay model, is needed for inference, even if only mean reaction delays are of interest. Using in silico and experimental data we show that the proposed hierarchical framework is robust and leads to improved estimates compared to its non-hierarchical counterpart. We apply our method to data obtained using time-lapse microscopy and infer the parameters that describe the dynamics of protein production at the single cell and population level. The mean delays in protein production are larger than previously reported, have a coefficient of variation of around 0.2 across the population, and are not strongly correlated with protein production or growth rates. AvailabilityAccompanying code in Python is available at https://github.com/mvcortez/Bayesian-Inference. Contactkresimir.josic@gmail.comkresimir.josic@gmail.com, jaekkim@kaist.ac.kr jaekkim@kaist.ac.kr, cbskust@korea.ac.kr cbskust@korea.ac.kr

systems biology↗

bioRxiv2021

Fuscimiditide: a RiPP with {Omega}-Ester and Aspartimide Post-translational Modifications

Microviridins and other {omega}-ester linked peptides (OEPs) are characterized by sidechain-sidechain linkages installed by ATP-grasp enzymes. Here we describe the discovery of a new family of OEPs, the gene clusters of which also encode an O-methyltransferase with homology to the protein repair catalyst protein L-isoaspartyl methyltransferase (PIMT). We produced the first example of this new ribosomally synthesized and post-translationally modified peptide (RiPP), fuscimiditide, via heterologous expression. NMR analysis of fuscimiditide revealed that the peptide contains two ester crosslinks forming a stem-loop macrocycle. Furthermore, an unusually stable aspartimide moiety is found within the loop macrocycle. We have also fully reconstituted fuscimiditide biosynthesis in vitro establishing that ester formation catalyzed by the ATP-grasp enzyme is an obligate, rate-limiting first biosynthetic step. Aspartimide formation from aspartate is catalyzed by the PIMT homolog in the second step. The aspartimide moiety embedded in fuscimiditide hydrolyzes regioselectively to isoaspartate (isoAsp). Surprisingly, this isoAsp-containing protein is also a substrate for the PIMT homolog, thus driving any hydrolysis products back to the aspartimide form. Whereas aspartimide is often considered a nuisance product in protein formulations, our data here suggest that some RiPPs have aspartimide residues intentionally installed via enzymatic activity. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=83 SRC="FIGDIR/small/444834v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@1c67f36org.highwire.dtl.DTLVardef@c9e774org.highwire.dtl.DTLVardef@17a7d62org.highwire.dtl.DTLVardef@bde61b_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2020

Repurposing the yeast peroxisome to compartmentalize a toxic enzyme enables improved (S)-reticuline production

Eukaryotic cells compartmentalize metabolic pathways in organelles to achieve optimal reaction conditions and avoid crosstalk with other factors in the cytosol. Increasingly, engineers are researching ways in which synthetic compartmentalization could be used to address challenges in metabolic engineering. Here, we identified that norcoclaurine synthase (NCS), the enzyme which catalyzes the first committed reaction in benzylisoquinoline alkaloid (BIA) biosynthesis, is toxic when expressed cytosolically in Saccharomyces cerevisiae and, consequently, restricts (S)-reticuline production. We developed a compartmentalization strategy that alleviates NCS toxicity while promoting increased (S)-reticuline titer, achieved through efficient targeting of toxic NCS to the peroxisome while, crucially, taking advantage of the free flow of metabolite substrates and product across the peroxisome membrane. We identified that peroxisome protein capacity in S. cerevisiae becomes a limiting factor for further improvement of BIA production and demonstrate that expression of engineered transcription factors can mimic the oleate response for larger peroxisomes, further increasing BIA titer without the requirement for peroxisome induction with fatty acids. This work specifically addresses the challenges associated with toxic NCS expression and, more broadly, highlights the potential for engineering organelles with desired characteristics for metabolic engineering.

synthetic biology↗

bioRxiv2020

Impact of metastatic prostate cancer on human bone marrow

Bone metastases are devastating complications of cancer. They are particularly common in prostate cancer, represent incurable disease and are refractory to immunotherapy. We sought to define distinct features of the bone marrow microenvironment by analyzing single cells from prostate cancer patients involved bone, uninvolved bone and distant bone sites as well as bone from cancer-free, orthopedic patients and healthy individuals. Metastatic prostate cancer was associated with multifaceted immune distortion, specifically exhaustion of distinct T cell subsets, appearance of macrophages with states specific to prostate cancer bone metastases. The chemokine CCL20 was notably overexpressed by myeloid cells, as was its cognate CCR6 receptor on T cells. Disruption of the CCL20-CCR6 axis in mice with syngeneic prostate bone metastases restored T cell reactivity and significantly prolonged animal survival. Comparative high resolution analysis of prostate cancer bone metastasis shows a targeted approach for relieving local immunosuppression for therapeutic effect.

cancer biology↗

bioRxiv2019

A yeast platform for high-level synthesis of natural and unnatural tetrahydroisoquinoline alkaloids

The tetrahydroisoquinoline (THIQ) moiety is a privileged substructure of many bioactive natural products and semi-synthetic analogues. The plant kingdom manufactures more than 3,000 THIQ alkaloids, including the opioids morphine and codeine. While microbial species have been engineered to synthesize a few compounds from the benzylisoquinoline alkaloid (BIA) family of THIQs, low product titers impede industrial viability and limit access to the full chemical space. Here we report a THIQ platform by increasing yeast production of the central BIA intermediate (S)-reticuline to more than 3 g L-1, a 38,000-fold improvement over our first-generation strain. Gains in BIA output coincided with the formation of several substituted THIQs derived from host amino acid catabolism. Enabled by this activity, we repurposed the yeast Ehrlich pathway and demonstrate the synthesis of an array of unnatural THIQ scaffolds. This work provides a blueprint for synthesizing new privileged structures and will enable the targeted overproduction of thousands of THIQ products, including natural and semi-synthetic opioids.

synthetic biology↗

bioRxiv2019

Cerebral perfusion and metabolism coupling during a critical time window provides rapid assessment of cardiac arrest severity and prognosis in a preclinical model

Improved quantitative understanding of the dynamic relationship among cerebral blood flow, oxygen consumption, and electrical activity is important to clinicians treating acute brain injury. Such knowledge would elucidate the neurovascular response to ischemia, helping to potentially guide treatment. Using a multimodal optical imaging platform and a clinically-relevant rat model of cardiac arrest (CA) and cardiopulmonary resuscitation (CPR), we continuously measured cerebral blood flow (CBF), brain tissue oxygenation (StO2), cerebral metabolic rate of oxygen (CMRO2), and cerebral electrical activity (electrocorticography; ECoG). Multiple phases of cerebral hemodynamic recovery, with different degrees of mismatch between CBF and CMRO2, were observed following CPR. At 1 min post-resuscitation, we observed that the ratio CBF/CMRO2 is indicative of CA duration/severity and prognostic (with 87% accuracy) of short-term neurological recovery measured by the re-initiation of ECoG activity. These measurements provide the earliest known metrics for assessment of CA severity and prognosis post-CPR. Interestingly, the accuracy of this information is lost beyond 2-3 minutes post-CPR, highlighting a critical, easily overlooked, period immediately post-CPR. These metrics do not require pre-resuscitation data, underscoring translational potential in emergency-response settings when pre-CA information is unavailable. These metrics encourage validation in human studies, potentially offering real-time feedback during CA/CPR to optimize neurological outcome.

neuroscience↗

bioRxiv2019

Spreading depolarization and repolarization during cardiac arrest as an ultra-early marker of neurological recovery in a preclinical model

Spreading depolarization (SD) accompanies numerous neurological conditions, including migraine, stroke, and traumatic brain injury. There is significant interest in understanding the relationship between SD and neuronal injury. However, characteristics underlying SD and repolarization (RP) induced by global cerebral ischemia (e.g., cardiac arrest (CA)) and reperfusion are not well understood. Quantifying features of SD and RP during CA and cardiopulmonary resuscitation (CPR) may provide important metrics for diagnosis and prognosis of neurological injury from hypoxia-ischemia. We characterized SD and RP in a rodent model of asphyxial CA+CPR using a multimodal platform including electrocorticography (ECoG) and optical imaging. We detected SD and RP by (1) alternating current (AC), (2) direct current (DC), and (3) optical imaging of spreading ischemia, spreading edema, and vasoconstriction. Earlier SD (r=-0.80; p<0.001) and earlier RP (r=-0.71, p<0.001) were associated with better neurological recovery after 24hrs. SD+RP onset times predicted good vs poor neurological recovery with 82% sensitivity and 91% specificity. To our knowledge, this is the first preclinical study to link SD and RP characteristics with neurological recovery post-CA. These data suggest that SD and RP may be ultra-early, real-time prognostic markers of post-CA outcome, meriting further investigation into translational implications during global cerebral ischemia.

neuroscience↗

bioRxiv2019

High-speed quantitative optical imaging of absolute metabolism in the rat cortex

Quantitative measures of blood flow and metabolism are essential for improved assessment of brain health and response to ischemic injury. In this report, we demonstrate a multimodal technique for measuring the cerebral metabolic rate of oxygen (CMRO2) in the rodent brain on an absolute scale (M O2 / min). We use laser speckle imaging (LSI) at 809 nm and spatial frequency domain imaging (SFDI) at 655 nm, 730 nm, and 850 nm to obtain spatiotemporal maps of cerebral blood flow (CBF), tissue absorption (a), and tissue scattering (s). Knowledge of these three values enables calculation of a characteristic blood flow speed, which in turn is input to a mathematical model with a \"zero-flow\" boundary condition to calculate absolute CMRO2. We apply this method to a rat model of cardiac arrest (CA) and cardiopulmonary resuscitation. With this model, the zero-flow condition occurs during entry into CA. The CMRO2 values calculated with our method are in good agreement with those measured with magnetic resonance (MR) and positron emission tomography (PET) by other groups. Our technique provides a quantitative metric of cerebral metabolism that can potentially be used for comparison between animals and longitudinal monitoring of a single animal over multiple days, to assess differences in baseline metabolism and track recovery of metabolism in survival studies following ischemia and reperfusion.

neuroscience↗

bioRxiv2019

Bayesian inference of distributed time delay in transcriptional and translational regulation

MotivationAdvances in experimental and imaging techniques have allowed for unprecedented insights into the dynamical processes within individual cells. However, many facets of intracellular dynamics remain hidden, or can be measured only indirectly. This makes it challenging to reconstruct the regulatory networks that govern the biochemical processes underlying various cell functions. Current estimation techniques for inferring reaction rates frequently rely on marginalization over unobserved processes and states. Even in simple systems this approach can be computationally challenging, and can lead to large uncertainties and lack of robustness in parameter estimates. Therefore we will require alternative approaches to efficiently uncover the interactions in complex biochemical networks.\n\nResultsWe propose a Bayesian inference framework based on replacing uninteresting or unobserved reactions with time delays. Although the resulting models are non-Markovian, recent results on stochastic systems with random delays allow us to rigorously obtain expressions for the likelihoods of model parameters. In turn, this allows us to extend MCMC methods to efficiently estimate reaction rates, and delay distribution parameters, from single-cell assays. We illustrate the advantages, and potential pitfalls, of the approach using a birth-death model with both synthetic and experimental data, and show that we can robustly infer model parameters using a relatively small number of measurements. We demonstrate how to do so even when only the relative molecule count within the cell is measured, as in the case of fluorescence microscopy.

systems biology↗

bioRxiv2018

Impact of Chronic Total Occlusion Lesion Length onSix-month Angiographic and 2-year Clinical Outcomes

BackgroundSuccessful chronic total occlusion (CTO) percutaneous coronary intervention (PCI) is known to be associated with improved clinical outcomes compared with failed CTO PCI. However, it is not clear whether the angiographic and clinical outcomes of long CTO lesionis different with those of short CTO lesion in the drug eluting stent (DES) era.\n\nMethod sand ResultsA total of 235 consecutive patients underwent successful CTO intervention were divided into two groups according the CTO lesion length. Six-month angiographic and two-year clinical outcomes were compared between the two groups. The baseline clinical characteristics were similar between the two groups except prior PCI was more frequent in long CTO group whereas bifurcation lesion was more frequent in the short CTO group. In-hospital complications were similar between the two groups except intimal dissection was more frequent in long CTO group. Both groups had similar angiographic outcomes at 6 months and clinical outcomes up to 2 years except the incidence of repeat PCI, predominantly target vessel revascularization (TVR) was higher in long CTO group. In multivariate analysis, long CTO was an important predictor for repeat PCI (OR;4.26, CI 1.53-11.9, p=0.006).\n\nConclusionThe safety profile, angiographic and 2-year clinical outcomes were similar between the two groups except higher incidence of repeat PCI in long CTO group despite of successful PCI with DESs.

physiology↗

bioRxiv2017

Beyond the Michaelis-Menten equation: Accurate and efficient estimation of enzyme kinetic parameters

Examining enzyme kinetics is critical for understanding cellular systems and for using enzymes in industry. The Michaelis-Menten equation has been widely used for over a century to estimate the enzyme kinetic parameters from reaction progress curves of substrates, which is known as the progress curve assay. However, this canonical approach works in limited conditions, such as when there is a large excess of substrate over enzyme. Even when this condition is satisfied, the identifiability of parameters is not always guaranteed, and often not verifiable in practice. To overcome such limitations of the canonical approach for the progress curve assay, here we propose a Bayesian approach based on an equation derived with the total quasi-steady-state approximation. In contrast to the canonical approach, estimates obtained with this proposed approach exhibit little bias for any combination of enzyme and substrate concentrations. Importantly, unlike the canonical approach, an optimal experiment to identify parameters with certainty can be easily designed without any prior information. Indeed, with this proposed design, the kinetic parameters of diverse enzymes with disparate catalytic efficiencies, such as chymotrypsin, fumarase, and urease, can be accurately and precisely estimated from a minimal amount of timecourse data. A publicly accessible computational package performing the Bayesian inference for such accurate and efficient enzyme kinetics is provided.

systems biology↗