Luis Cisneros
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1001 S. McAllister Ave Biodesign Institute, A130A Tempe, AZ 85287
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My research interests revolve around studies of the mechanisms governing the emergence of collective behavior in complex systems, with emphasis in spatial organization and distributed information dynamics driving adaptive responses of groups of interacting units, in particular living systems.
During my doctoral studies at Dr. Goldstein’s lab at the University of Arizona, my work focused on the collective behavior of swarming, self-propelled bacteria. This research elucidated the intricate relationships between body alignment, coherent motion, and cell concentration that characterize the ”flocking” behavior of these microorganisms. An important implication of this research was that collective responses in cellular systems can arise from the dynamic interactions of cells with each other and their environment, rather than ad hoc centralized controls. Recognizing the significance of these collective responses in fostering the long-term adaptive potential and persistence of cell populations in changing environments, leading to multicellularity, became a driving force for my ongoing research.
In my postdoctoral role, I adopted a systems-biology perspective to explore cancer as a breakdown of multicellularity. This involved studying neoplasms and their transition from organismal-level selection to cellular-level processes, fostering cell heterogeneity and competition - a journey inverse to the evolution of multicellularity. As part of Dr. Paul Davies’ team in the ASU-PSOC program, I developed a metastasis model that highlighted the role of rare event dynamics in early organ invasion, underscoring the importance of spatial diversity, and niche construction in disease progression. In collaboration with Dr. Kimberly Bussey, our bioinformatic studies uncovered an evolutionary signature in cancer genomes, showcasing the robustness of ancient genes and their association with advanced stages of cancer. This work unveiled a signature of stress-induced mutagenesis in cancer cells, an ancestral mechanism of evolvability and diversification that predates multicellularity.
In collaboration with Dr. Julia Bos from the Institut Pasteur in Paris, I explored the dispersion process of membrane vesicles in bacteria challenged with antibiotic stress. This research revealed critical details in the emergence of drug resistance, offering insights not only into clinically relevant antibiotic-resistance issues, but also analogous cancer adaptive response mechanisms. My current work at Dr. Carlo Maley’s ASU lab focuses on the evolution of resistance to therapy. While tumors are widely acknowledged as ecological and evolutionary processes of cell populations, there remains a gap in drawing clinically relevant distinctions that could identify how cancer cells adapt to drugs, and how to manipulate such mechanisms to achieve optimal patient benefits. A pivotal direction in this research involves translating well-established spatial statistics methods, from landscape ecology and geographical information systems methodologies, into the analysis of cancer samples. This approach allows for the exploration of the ecological aspects of tumor micro-environments using digitalized cell location data from histopathological images, providing a nuanced understanding of spatial heterogeneity, complexity, and evolutionary dynamics in populations of cancer cells. Another facet of this work involves building theoretical and computational models representing the spatial dynamics, phenotypic heterogeneity, and evolution dynamics of populations of cancer cells. These models enable the assessment of disease response to different therapeutic conditions. The ultimate goal is the optimization of therapeutic dosage modulation to maximize control over tumor growth, eliminate the competitive release of resistant mutants, prolong the expected time to recurrence, and minimize the negative effects of treatment. The study of therapy resistance evolution remains a focal point of my research due to its significant clinical implications.
Additionally I have participated in a diverse set of other lines of research, most notably modeling of urban dynamics in collaboration with anthropologist Thomas Park from the University of Arizona, and development of bioinformatic measures of RNAseq transcript integrity and co-expression patterns of genomic elements while working in NantOmics.
1. Top-Down Causation effect: During my graduate research with Dr. Juan Jimenez at the Universidad Central de Venezuela I developed statistical methods that showed that the progression to a collective phase in a network of coupled dynamical elements is characterized by a sharp transition in the information that flows from the macroscopic scales into microscopic scales of the system. This work was seminal in suggesting that self-organization in complex systems develops when individual parts carry complete information about the global dynamics and is now described as the Top-Down Causation effect.
a. Cisneros L, Jiménez J, Cosenza M and Parravano A: Information transfer and nontrivial collective behavior in chaotic coupled map networks. Physical Review E, 65: 045204(R), 2002
b. Walker SI, Cisneros L and Davies PCW: Evolutionary Transitions and Top-Down Causation. Proceedings of Artificial Life, 13: 283-290, 2012
2. Biofluid dynamics of self-propelled microorganisms: During my doctoral work with Raymond Goldstein at the University of Arizona, I participated in their groundbreaking research on the collective behavior of swarming rod-like self-propelled bacteria B. subtilis. When these microorganisms are in concentrated conditions, local body alignments and hydrodynamics conditions allow for coherent motion bringing forward large-scale patterns akin to the flocking phenomena observed in fish schools or bird flocks. I combined microfluidic experiments using fluorescence microscopy, developed image processing methods, and analysis tools to achieve a comprehensive characterization of the collective phase of bacterial suspensions under different conditions. I also produced simulations and theoretical models that helped elucidate the relationships between alignment, coherent motion, and cell concentration in the collective phase. Some important implications of this work are that when cells engage in such collective behavior, they increase their chances of survival as a community. For instance, coherent swimming motion causes faster transport of oxygen or nutrients in the cellular medium, allows them to share their individual risks, or organize in biofilm-forming structures, thus providing primitive forms of division of labor. This work is important in showing how physical constraints might drive early multicellularity, showing that the collective response of cell colonies can have adaptive capacity and that this process can be codified in the network of cell interactions and their ecological context, rather than programmed behavior of individual microorganisms.
a. Dombrowski C, Cisneros L, Chatkaew S, Kessler JO, and Goldstein RE.: Self-Concentration and Large-Scale Coherence in Bacterial Dynamics. Physical Review Letters, 93: 098103, 2004
b. Tuval I, Cisneros L, Dombrowski C, Wolgemuth CW, Kessler JO, and Goldstein RE: Bacterial Swimming and Oxygen Transport Near Contact Lines. Proceedings of the National Academy of Sciences, 102: 2277-2282, 2005
c. Cisneros L, Kessler JO, Sujoy Ganguly S and Goldstein RE: Dynamics of swimming bacteria: Transition to directional order at high concentration. Physical Review E, 83:061907, 2011
d. Cisneros L, Kessler JO, Sujoy Ganguly S and Goldstein RE: Individual to Collective Dynamics of Swimming Bacteria, in Natural locomotion in fluids and on surfaces: Swimming, flying, and sliding. IMA Volume. Springer. New York, 2012.
3. Quantifying metastatic inefficiency: my theoretical work with Dr. Newman of the University of Dundee produced a very interesting result concerning metastatic inefficiency. Taking a simple stochastic birth-death process approach to model the early stages of metastatic invasion, we conjectured that as a tumor grows from a single seeding cell, it will eventually be large enough to establish its internal microenvironment (the critical size at which interior cells are physically protected), but before then, cells would be susceptible to apoptotic signals or immune surveillance from the surrounding tissue. Our model suggested that in the context of a large number of invasive attempts, rare event statistics, rather than a selective advantage, can be sufficient for a small number of successful micro-tumors to emerge in a patient with metastatic disease. Rigorous mathematical modeling showed that the expected waiting time of these rare micro-tumors scales exponentially with the inverse of the critical size but only linearly with the inverse of the constitutive cell fitness. Therefore, any small modification of the conditions that determine the critical size would translate into a significant lengthening of the life expectancy of a patient undergoing metastasis, suggesting the tissue microenvironment, and thus conditions of the cell ecology, are paramount therapeutic targets.
a. Cisneros L and Newman T: Quantifying metastatic inefficiency: rare genotypes versus rare dynamics. Physical Biology, 11: 046003, 2014.
4. Stress-induced mutagenesis is a cancer phenotype: my bioinformatic work on publicly available cancer data correlated gene evolutionary ages with the observed patterns of mutations in whole-genome sequencing data and patterns of expression changes. In particular, my collaboration with Dr. Bussey yielded a collection of (patented) bioinformatics methodologies to detect mutational signatures of stress-induced mutagenesis in whole-genome sequencing of cancer samples, a conserved ancestral biological mechanism of diversification that could be engaged in cancer samples and be determinant in the progression of the disease, response to therapy and recurrence.
a. Cisneros L, Bussey KJ. and C Vasque: Identification of a signature of evolutionarily conserved stress-induced mutagenesis in cancer. bioRxiv 2021.04.17.440291(article under review)
b. Cisneros L, Bussey KJ, Orr A, Miocevic M, Lineweaver CH and Davies P: Ancient genes establish stress-induced mutation as a hallmark of cancer. Plos ONE, 12: e0176258, 2017.
c. Zhou JX, Cisneros L, Knijnenburg T, Trachana K, Davies P and Huang S.: Phylostratigraphic analysis of tumor and developmental transcriptomes reveals relationship between oncogenesis, phylogenesis and ontogenesis. Convergent Science Physical Oncology, 4:025002, 2018
d. Bussey KJ, Cisneros L, Lineweaver CH, Davies P: Ancestral gene regulatory networks drive cancer. Proceedings of the National Academy of Sciences, 114:6160, 2017.
5. Dynamics of bacterial membrane vesicles: Membrane vesicles are ubiquitous carriers of molecular information. My work with Dr. Julia Bos provided a quantitative analysis of the motion of individual vesicles in living microbes using fluorescence microscopy, showing that when bacteria are challenged with low doses of antibiotics, vesicle production and traffic, quantified by instantaneous vesicle speeds and total traveled distance per unit time, are significantly enhanced. Our results provide insights into the spatial organization and dynamics of membrane vesicles in microcolonies during the process of adaptation to drugs.
a. Bos J, Cisneros LH, Mazel D. Real-time tracking of bacterial membrane vesicles reveals enhanced membrane traffic upon antibiotic exposure. Sci Adv. 2021 Jan 20;7(4):eabd1033.