Fabian Santiago’s research while affiliated with University of California, Merced and other places

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Publications (9)


Proposed mechanisms of TFPI inhibition of factor X activation
In 1998, Baugh et al. [9] proposed a scheme with two reaction pathways for TFPI inhibition of factor X activation: direct and indirect. In our work, we consider a modification of Baugh’s scheme by restricting it to elementary reactions only and removing the multi-step reaction 5. (A) Representative structures for coagulation factors and associated labels. (B) Biochemical reactions involved in the direct inhibition of factor X activation. (C) Biochemical reactions involved in the indirect inhibition of factor X activation. (D) Schematic for the reactions involved in the activation of factor X by TF:VIIa and both the direct and indirect pathways of inhibition by TFPI.
Experimental measurements and uncertainty in model predictions of factor X activation
(A) Factor X (170 nM) activated by TF:VIIa (0.032 to 1.024 nM) in the presence of TFPI (2.4 nM). (B) Factor X (170 nM) activated by TF:VIIa (0.128 nM) in the presence of TFPI (2.4 nM), preincubated with factor Xa (0.00 to 1.00 nM). Data extracted from Figure 3B of [9]. The curves show model predictions using median and literature values presented in Table 1, and the uncertainty in model predictions using posterior estimates (see S1 and S2 Figs): 70%, 90%, and 99% credible intervals about the median model prediction. Note that there is a replicate experimental condition between both experiments. The Xa = 0 nM pre-incubation condition in Experiment Two (B) matches the TFPI 0.128 nM curve in Experiment One (A).
Inhibition of factor X activation under flow
During the early phase of the coagulation cascade, clotting factor X (denoted as S) is activated by the surface-bound TF:VIIa complex (denoted as E), as shown in the pathway labeled ‘No TFPI.’ Tissue Factor Pathway Inhibitor (TFPI, denoted as I), also brought in by flow, inhibits this activation. Initially, TFPI forms the transient E:P:I complex with the E complex and activated factor X (denoted as P). This complex rapidly undergoes a conformational change to form a stable P:I:E complex, depicted as ‘Direct Binding.’ Additionally, TFPI can inhibit factor X activation through a second mechanism, starting with the formation of the P:I complex. This complex subsequently binds to the E complex, forming the transient E:P:I complex that also transitions into the stable P:I:E configuration, as illustrated in the ‘Indirect Binding’ pathway.
Functional enzyme over time by inhibition pathway
Concentration of functional enzyme over time by pathway of inhibition, for (A) low flow (kflow = 10⁻³ s⁻¹), (B) medium flow (kflow = 10⁰ s⁻¹), and (C) high flow (kflow = 10³ s⁻¹).
Functional enzyme at steady state over flow rate
For each model, the steady state concentration of functional enzyme ([E] and [E:S]) is presented for flow rates from 10⁻³ (Low Flow) to 10³ sec⁻¹ (High Flow).

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A new look at TFPI inhibition of factor X activation
  • Article
  • Full-text available

November 2024

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16 Reads

Fabian Santiago

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Amandeep Kaur

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Shannon Bride

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[...]

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Blood coagulation is a vital physiological process involving a complex network of biochemical reactions, which converge to form a blood clot that repairs vascular injury. This process unfolds in three phases: initiation, amplification, and propagation, ultimately leading to thrombin formation. Coagulation begins when tissue factor (TF) is exposed on an injured vessel’s wall. The first step is when activated factor VII (VIIa) in the plasma binds to TF, forming complex TF:VIIa, which activates factor X. Activated factor X (Xa) is necessary for coagulation, so the regulation of its activation is crucial. Tissue Factor Pathway Inhibitor (TFPI) is a critical regulator of the initiation phase as it inhibits the activation of factor X. While previous studies have proposed two pathways—direct and indirect binding—for TFPI’s inhibitory role, the specific biochemical reactions and their rates remain ambiguous. Many existing mathematical models only assume an indirect pathway, which may be less effective under physiological flow conditions. In this study, we revisit datasets from two experiments focused on activated factor X formation in the presence of TFPI. We employ an adaptive Metropolis method for parameter estimation to reinvestigate a previously proposed biochemical scheme and corresponding rates for both inhibition pathways. Our findings show that both pathways are essential to replicate the static experimental results. Previous studies have suggested that flow itself makes a significant contribution to the inhibition of factor X activation. We added flow to this model with our estimated parameters to determine the contribution of the two inhibition pathways under these conditions. We found that direct binding of TFPI is necessary for inhibition under flow. The indirect pathway has a weaker inhibitory effect due to removal of solution phase inhibitory complexes by flow.

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FIGURE 2 The [PSI + ] Weak variant persists after mating to the dominant [PSI + ] Strong variant. (A) Wildtype (WT) [psi − ], [PSI + ] Weak , and [PSI + ] Strong haploids were mated to a WT [PSI + ] Strong haploid without treatment (untreated, dark gray), in the presence of 3 mM GdnHCl (treated, light gray), and in the presence of 3 mM GdnHCl following growth of the [PSI + ] Strong haploid (1N) in the presence of GdnHCl for 12 h (titrated, white). The number of [PSI + ] Strong propagons from the resulting zygotes and a [PSI + ] Strong haploid was quantified and presented as box-whisker plots. Horizontal lines indicate 25th, 50th, and 75th percentiles; whiskers indicate 10th and 90th percentiles; diamonds indicate means; outliers are presented as dots. The number of zygotes analyzed is presented in parentheses below each box plot. The equality of means across all groups was tested using Welch's ANOVA test (p* ANOVA ); p-values were determined using pairwise unequal variance t-tests and are presented above each box plot for comparisons within a cross. The absence of a p-value for comparisons within a cross indicates a lack of significant difference. Full statistical comparisons are available in Supplementary Table S3. (B) The number of [PSI + ] Weak propagons from the zygotes presented in (A) was quantified and presented as box-whisker plots as in (A). The equality of means across all groups was tested using Welch's ANOVA test (p* ANOVA ); p-values were determined using pairwise unequal variance t-tests and are presented above each box plot for comparisons within a cross. The absence of a p-value for comparisons within a cross indicates a lack of significant difference. Full statistical comparisons are available in Supplementary Table S4. (C) The persistence of the [PSI + ] Weak variant was observed by microscopy in crosses between [PSI + ] Strong and [PSI + ] Weak haploids expressing Sup35(G20D)-GFP under the control of the P tetO7 promoter. GFP foci were detected in cells at the periphery of the resulting microcolony, indicated by white arrows in the inset (200-fold magnification).
FIGURE 4 The dominant [PSI + ] Strong variant competes for soluble Sup35 more efficiently than the recessive [PSI + ] Weak variant. (A) Wildtype [PSI + ] Strong (blue) and [PSI + ] Weak haploids (salmon) were mated to a [PSI + ] Weak haploid expressing GFP-tagged Sup35 under the control of the P MFA1 promoter. Fluorescence intensity was quantified in the mother lobe of a singly budded zygote following repeated photobleaching of the daughter (left), and the rate of fluorescence loss was calculated and presented as box-whisker plots (right, n ≥ 11). Horizontal lines indicate 25th, 50th, and 75th percentiles; whiskers indicate 10th and 90th percentiles; diamonds indicate means. An unequal variance t-test was used to determine p values (B) A [PSI + ] Weak haploid expressing a GFP-tagged Sup35 mutant (G20D) under the control of the P MFA1 promoter was mated to wildtype [PSI + ] Strong (blue) and [PSI + ] Weak (salmon) haploids and analyzed as in (A, n ≥ 13).
Bacterial plasmids.
Oligonucleotides.
Multiple aspects of amyloid dynamics in vivo integrate to establish prion variant dominance in yeast

July 2024

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15 Reads

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2 Citations

Frontiers in Molecular Neuroscience

Prion variants are self-perpetuating conformers of a single protein that assemble into amyloid fibers and confer unique phenotypic states. Multiple prion variants can arise, particularly in response to changing environments, and interact within an organism. These interactions are often competitive, with one variant establishing phenotypic dominance over the others. This dominance has been linked to the competition for non-prion state protein, which must be converted to the prion state via a nucleated polymerization mechanism. However, the intrinsic rates of conversion, determined by the conformation of the variant, cannot explain prion variant dominance, suggesting a more complex interaction. Using the yeast prion system [PSI⁺], we have determined the mechanism of dominance of the [PSI⁺]Strong variant over the [PSI⁺]Weak variant in vivo. When mixed by mating, phenotypic dominance is established in zygotes, but the two variants persist and co-exist in the lineage descended from this cell. [PSI⁺]Strong propagons, the heritable unit, are amplified at the expense of [PSI⁺]Weak propagons, through the efficient conversion of soluble Sup35 protein, as revealed by fluorescence photobleaching experiments employing variant-specific mutants of Sup35. This competition, however, is highly sensitive to the fragmentation of [PSI⁺]Strong amyloid fibers, with even transient inhibition of the fragmentation catalyst Hsp104 promoting amplification of [PSI⁺]Weak propagons. Reducing the number of [PSI⁺]Strong propagons prior to mating, similarly promotes [PSI⁺]Weak amplification and conversion of soluble Sup35, indicating that template number and conversion efficiency combine to determine dominance. Thus, prion variant dominance is not an absolute hierarchy but rather an outcome arising from the dynamic interplay between unique protein conformations and their interactions with distinct cellular proteostatic niches.


Modeling and Global Sensitivity Analysis of Strategies to Mitigate Covid-19 Transmission on a Structured College Campus

January 2023

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65 Reads

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1 Citation

Bulletin of Mathematical Biology

In response to the COVID-19 pandemic, many higher educational institutions moved their courses on-line in hopes of slowing disease spread. The advent of multiple highly-effective vaccines offers the promise of a return to “normal” in-person operations, but it is not clear if—or for how long—campuses should employ non-pharmaceutical interventions such as requiring masks or capping the size of in-person courses. In this study, we develop and fine-tune a model of COVID-19 spread to UC Merced’s student and faculty population. We perform a global sensitivity analysis to consider how both pharmaceutical and non-pharmaceutical interventions impact disease spread. Our work reveals that vaccines alone may not be sufficient to eradicate disease dynamics and that significant contact with an infectious surrounding community will maintain infections on-campus. Our work provides a foundation for higher-education planning allowing campuses to balance the benefits of in-person instruction with the ability to quarantine/isolate infectious individuals. Supplementary Information The online version contains supplementary material available at 10.1007/s11538-022-01107-2.


A structured model and likelihood approach to estimate yeast prion propagon replication rates and their asymmetric transmission

July 2022

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3 Reads

Prion proteins cause a variety of fatal neurodegenerative diseases in mammals but are generally harmless to Baker’s yeast (Saccharomyces cerevisiae). This makes yeast an ideal model organism for investigating the protein dynamics associated with these diseases. The rate of disease onset is related to both the replication and transmission kinetics of propagons, the transmissible agents of prion diseases. Determining the kinetic parameters of propagon replication in yeast is complicated because the number of propagons in an individual cell depends on the intracellular replication dynamics and the asymmetric division of yeast cells within a growing yeast cell colony. We present a structured population model describing the distribution and replication of prion propagons in an actively dividing population of yeast cells. We then develop a likelihood approach for estimating the propagon replication rate and their transmission bias during cell division. We first demonstrate our ability to correctly recover known kinetic parameters from simulated data, then we apply our likelihood approach to estimate the kinetic parameters for six yeast prion variants using propagon recovery data. We find that, under our modeling framework, all variants are best described by a model with an asymmetric transmission bias. This demonstrates the strength of our framework over previous formulations assuming equal partitioning of intracellular constituents during cell division.


Modeling and Global Sensitivity Analysis of Strategies to Mitigate Covid-19 Transmission on a Structured College Campus

April 2022

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36 Reads

In response to the COVID-19 pandemic, many higher educational institutions moved their courses on-line in hopes of slowing disease spread. The advent of multiple highly-effective vaccines offers the promise of a return to "normal" in-person operations, but it is not clear if -- or for how long -- campuses should employ non-pharmaceutical interventions such as requiring masks or capping the size of in-person courses. In this study, we develop and fine-tune a model of COVID-19 spread to UC Merced's student and faculty population. We perform a global sensitivity analysis to consider how both pharmaceutical and non-pharmaceutical interventions impact disease spread. Our work reveals that vaccines alone may not be sufficient to eradicate disease dynamics and that significant contact with an infected surrounding community will maintain cases on-campus. Our work provides a foundation for higher-education planning allowing campuses to balance the benefits of in-person instruction with the ability to quarantine/isolate infected individuals.


Molecular Surveillance and Assessment of Ceftolozane/Tazobactam Resistance with Common β-Lactam Antibiotics and β-Lactamase Genes

September 2021

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15 Reads

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1 Citation

Ceftolozane/tazobactam (c/t) is a potent β-lactam antibiotic which combines the fifth generation cephalosporin ceftolozane and tazobactam, a β-lactamase inhibitor. The c/t combination therapy was approved in 2014 for the treatment of multidrug resistant (MDR) Enterobacteriaceae, especially intra-abdominal and urinary tract infections. The aim of this study is to assess c/t activity and to examine the association of c/t resistance with four common β-lactamase resistance genes found in clinical Enterobacteriaceae isolates collected from mainly urinary tract infections in an agricultural region in California (USA) between 2013-2020. We tested 993 Extended Spectrum β-lactamases (ESBL) producing Enterobacteriaceae isolates (885 E. coli, 94 K. pneumoniae, 14 other) for c/t susceptibility by Kirby-Bauer disk diffusion and screened using PCR for four common resistance genes with β-lactamase activity(blaTEM, blaOXA, blaSHV, and blaCTX-M) for 855 of the isolates. We also investigated co-resistance of c/t and nine other β-lactam antibiotics. We found that most isolates were susceptible to c/t (58.3%), while 38.5% showed intermediate resistance, and 3.2% were resistant. We also found that K. pneumoniae isolates were more resistant to c/t than E. coli isolates, and that c/t may be a good alternative to carbapenems, in that that some carbapenem resistant isolates were susceptible to c/t. Genotypic analysis showed blaSHV and blaCTX-M are independently associated with elevated c/t resistance. Although c/t demonstrated strong activity against Enterobacteriaceae, the high percentage of isolates with intermediate susceptibility emphasizes the need for close monitoring and continued surveillance for c/t resistance among ESBLs


Venn diagrams of blaSHV, blaTEM, blaCTX-M, and blaOXA combinations from both repositories. (a) Venn diagram of the resistance genes found in the clinical isolates from DHMMC. There were 142 isolates without any of these resistance genes (inconclusive data). (b) Venn diagram of the resistance genes found in the nationwide database of ESBL clinical isolates.
Distribution of β-Lactamase Genes in Clinical Isolates from California Central Valley Hospital Deviates from the United States Nationwide Trends

The evolution and dissemination of antibiotic resistance genes throughout the world are clearly affected by the selection and migration of resistant bacteria. However, the relative contributions of selection and migration at a local scale have not been fully explored. We sought to identify which of these factors has the strongest effect through comparisons of antibiotic resistance gene abundance between a distinct location and its surroundings over an extended period of six years. In this work, we used two repositories of extended spectrum β-lactamase (ESBL)-producing isolates collected since 2013 from patients at Dignity Health Mercy Medical Center (DHMMC) in Merced, California, USA, and a nationwide database compiled from clinical isolate genomes reported by the National Center for Biotechnology Information (NCBI) since 2013. We analyzed the stability of average resistance gene frequencies over the years since collection of these clinical isolates began for each repository. We then compared the frequencies of resistance genes in the DHMMC collection with the averages of the nationwide frequencies. We found DHMMC gene frequencies are stable over time and differ significantly from nationwide frequencies throughout the period of time we examined. Our results suggest that local selective pressures are a more important influence on the population structure of resistance genes in bacterial populations than migration. This, in turn, indicates the potential for antibiotic resistance to be controlled at a regional level, making it easier to limit the spread through local stewardship.


Numerical Approaches to Division and Label Structured Population Models

November 2020

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22 Reads

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3 Citations

Letters in Biomathematics

Division and label structured population models (DLSPMs) are a class of partial differential equations (PDEs) that have been used to study intracellular dynamics in dividing cells. DLSPMs have improved the understanding of cell proliferation assays involving measurements such as fluorescent label decay, protein production, and prion aggregate amplification. One limitation in using DLSPMs is the significant computational time required for numerical approximations, especially for models with complex biologically relevant dynamics. Here we develop a novel numerical and theoretical framework involving a recursive formulation for a class of DLSPMs. We develop this framework for a population of dividing cells with an arbitrary functional form describing the intracellular dynamics. We found that, compared to previous methods, our framework is faster and more accurate. We illustrate our approach on three common models for intracellular dynamics and discuss the potential impact of our findings in the context of data-driven methods for parameter estimation.


Growth rate assays reveal fitness consequences of β-lactamases

January 2020

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123 Reads

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3 Citations

Antibiotic resistance is a powerful model for studying evolutionary biology and population genetics. For the purpose of these evolutionary studies, fitness data have been approximated through susceptibility testing methods designed for clinical use in providing appropriate antibiotic therapies. An alternative approach for measuring fitness of microbes has experienced growing popularity: growth rates are a highly sensitive approach for measuring the fitness effects of antibiotics and resistance genes, but they differ from susceptibility testing in that a single concentration of antibiotic is used for the assay. Here we show that despite this key difference, the results of growth rates correlate well with clinical determination of resistance by minimum inhibitory concentration (MIC), while providing the sensitivity required for direct input as fitness values into mathematical models. This means that growth rates at a single sublethal inhibitory concentration can help us understand the fitness effects that result in clinical antibiotic resistance. By measuring the growth rates of sequenced clinical isolates obtained from Dignity Health Mercy Medical Center, we detected the fitness effects of individual resistance genes on bacteria exposed to different antibiotics. In our study, the CTX-M-15 gene conferred the highest fitness in assays with cephalosporins. These results show the strong fitness benefit conferred by CTX-M-15. Non-technical summary Antibiotic resistance is a global human health problem. We partnered with Dignity Health Mercy Medical Center to study antibiotic resistance in clinical isolates. We tested whether growth rates, a sensitive assay used to measure the fitness of bacterial samples, correlate with a clinical test to measure antibiotic resistance. We found a strong correlation between these two methods suggesting that growth rates could be reliably applied to evolutionary studies of clinically relevant problems. Moreover, the sensitivity of the growth rates assay enabled us to identify fitness effects of specific antibiotic resistance genes.

Citations (4)


... Higher-token Petri net computad projects could include: • Categorical Alzheimer's dynamics (Norton et al. 2024) • Enzyme kinetics (Michaelis-Menten) for epigenetic mutation and damage repair rates (Bardini et al. 2016) • 2-Segal space immune pathway analysis (Lin et al. 2024) • AQFT-FQFT field theory of senescent cell clearance • Feynman category fibration analysis of inflammaging • Open Petri net model of longevity SIR (Baez et al. 2022) ...

Reference:

Categorical Longevity: Higher Tokens, Petri Net Computads, and Well-being
Multiple aspects of amyloid dynamics in vivo integrate to establish prion variant dominance in yeast

Frontiers in Molecular Neuroscience

... By utilizing advanced microbiological techniques, including culture and molecular methods, the research will enhance the detection of a wide range of uropathogens, thereby providing a more comprehensive understanding of the microbial landscape associated with UTIs [15,16]. The ndings from this study are expected to contribute signi cantly to the existing body of literature on UTIs, offering valuable insights that can guide clinical practice and public health strategies aimed at mitigating the impact of antimicrobial resistance [17,18]. This study is designed to address the urgent need for a deeper understanding of the factors contributing to multidrug resistance in UTIs among female patients. ...

Molecular Surveillance and Assessment of Ceftolozane/Tazobactam Resistance with Common β-Lactam Antibiotics and β-Lactamase Genes
  • Citing Article
  • September 2021

... The main goal of current study was to determine the level of knowledge and application regarding standard precautions of infection and acute injuries and determine the association between knowledge level and application level [20,21] . ...

Numerical Approaches to Division and Label Structured Population Models
  • Citing Article
  • November 2020

Letters in Biomathematics

... In this approach, growth parameters, such as the maximum growth rate (V max ), carrying capacity (K), and area under the curve (AUC), are calculated from absorbance values and used as proxies for fitness (Kugelberg et al. 2005;Hansen et al. 2007;Hegreness et al. 2008;Paulander et al. 2009;McDonald et al. 2012; Handling Editor: Kerry Geiler-Samerotte. Ketola and Saarinen 2015;Kang et al. 2019;Santiago et al. 2020;Frey et al. 2021). Populations with increased V max , K, or AUC values are considered to be more fit relative to those with lower values. ...

Growth rate assays reveal fitness consequences of β-lactamases