The analysis of living systems can generate both knowledge and illusions

Selecting genes for analysis using historically contingent progress: from RNA changes to protein-protein interactions

Progress in biology has generated numerous lists of genes that share some property. But advancing from these lists of genes to understanding their roles is slow and unsystematic. Here we use RNA silencing in C. elegans to illustrate an approach for prioritizing genes for detailed study given limited resources. The partially subjective relationships between genes forged by both deduced functional relatedness and biased progress in the field was captured as mutual information and used to cluster genes that were frequently identified yet remain understudied. Some proteins encoded by these understudied genes are predicted to physically interact with known regulators of RNA silencing, suggesting feedback regulation. Predicted interactions with proteins that act in other processes and the clustering of studied genes among the most frequently perturbed suggest regulatory links connecting RNA silencing to other processes like the cell cycle and asymmetric cell division. Thus, among the gene products altered when a process is perturbed could be regulators of that process acting to restore homeostasis, which provides a way to use RNA sequencing to identify candidate protein-protein interactions. Together, the analysis of perturbed transcripts and potential interactions of the proteins they encode could help prioritize candidate regulators of any process.

Heritable epigenetic changes are constrained by the dynamics of regulatory architectures

Interacting molecules create regulatory architectures that can persist despite turnover of molecules. Although epigenetic changes occur within the context of such architectures, there is limited understanding of how they can influence the heritability of changes. Here, I develop criteria for the heritability of regulatory architectures and use quantitative simulations of interacting regulators parsed as entities, their sensors, and the sensed properties to analyze how architectures influence heritable epigenetic changes. Information contained in regulatory architectures grows rapidly with the number of interacting molecules and its transmission requires positive feedback loops. While these architectures can recover after many epigenetic perturbations, some resulting changes can become permanently heritable. Architectures that are otherwise unstable can become heritable through periodic interactions with external regulators, which suggests that mortal somatic lineages with cells that reproducibly interact with the immortal germ lineage could make a wider variety of architectures heritable. Differential inhibition of the positive feedback loops that transmit regulatory architectures across generations can explain the gene-specific differences in heritable RNA silencing observed in the nematode Caenorhabditis elegans. More broadly, these results provide a foundation for analyzing the inheritance of epigenetic changes within the context of the regulatory architectures implemented using diverse molecules in different living systems.

Heritable epigenetic changes are constrained by the dynamics of regulatory architectures

Interacting molecules create regulatory architectures that can persist despite turnover of molecules. Although epigenetic changes occur within the context of such architectures, there is limited understanding of how they can influence the heritability of changes. Here I develop criteria for the heritability of regulatory architectures and use quantitative simulations of interacting regulators parsed as entities, their sensors and the sensed properties to analyze how architectures influence heritable epigenetic changes. Information contained in regulatory architectures grows rapidly with the number of interacting molecules and its transmission requires positive feedback loops. While these architectures can recover after many epigenetic perturbations, some resulting changes can become permanently heritable. Such stable changes can (1) alter steady-state levels while preserving the architecture, (2) induce different architectures that persist for many generations, or (3) collapse the entire architecture. Architectures that are otherwise unstable can become heritable through periodic interactions with external regulators, which suggests that the evolution of mortal somatic lineages with cells that reproducibly interact with the immortal germ lineage could make a wider variety of regulatory architectures heritable. Differential inhibition of the positive feedback loops that transmit regulatory architectures across generations can explain the gene-specific differences in heritable RNA silencing observed in the nematode C. elegans, which range from permanent silencing to recovery from silencing within a few generations and subsequent resistance to silencing. More broadly, these results provide a foundation for analyzing the inheritance of epigenetic changes within the context of the regulatory architectures implemented using diverse molecules in different living systems.

Albumin Uptake and Processing by the Proximal Tubule: Physiologic, Pathologic and Therapeutic Implications

For nearly 50 years the proximal tubule (PT) has been known to reabsorb, process, and either catabolize or transcytose albumin from the glomerular filtrate. Innovative techniques and approaches have provided insights into these processes. Several genetic diseases, nonselective PT cell defects, chronic kidney disease (CKD), and acute PT injury lead to significant albuminuria, reaching nephrotic range. Albumin is also known to stimulate PT injury cascades. Thus, the mechanisms of albumin reabsorption, catabolism, and transcytosis are being reexamined with the use of techniques that allow for novel molecular and cellular discoveries. Megalin, a scavenger receptor, cubilin, amnionless, and Dab2 form a nonselective multireceptor complex that mediates albumin binding and uptake and directs proteins for lysosomal degradation after endocytosis. Albumin transcytosis is mediated by a pH-dependent binding affinity to the neonatal Fc receptor (FcRn) in the endosomal compartments. This reclamation pathway rescues albumin from urinary losses and cellular catabolism, extending its serum half-life. Albumin that has been altered by oxidation, glycation, or carbamylation or because of other bound ligands that do not bind to FcRn traffics to the lysosome. This molecular sorting mechanism reclaims physiological albumin and eliminates potentially toxic albumin. The clinical importance of PT albumin metabolism has also increased as albumin is now being used to bind therapeutic agents to extend their half-life and minimize filtration and kidney injury. The purpose of this review is to update and integrate evolving information regarding the reabsorption and processing of albumin by proximal tubule cells including discussion of genetic disorders and therapeutic considerations.

Teaching computational systems biology with an eye on quantitative systems pharmacology at the undergraduate level: Why do it, who would take it, and what should we teach?

Computational systems biology (CSB) is a field that emerged primarily as the product of research activities. As such, it grew in several directions in a distributed and uncoordinated manner making the area appealing and fascinating. The idea of not having to follow a specific path but instead creating one fueled innovation. As the field matured, several interdisciplinary graduate programs emerged attempting to educate future generations of computational systems biologists. These educational initiatives coordinated the dissemination of information across student populations that had already decided to specialize in this field. However, we are now entering an era where CSB, having established itself as a valuable research discipline, is attempting the next major step: Entering undergraduate curricula. As interesting as this endeavor may sound, it has several difficulties, mainly because the field is not uniformly defined. In this manuscript, we argue that this diversity is a significant advantage and that several incarnations of an undergraduate-level CSB biology course could, and should, be developed tailored to programmatic needs. In this manuscript, we share our experiences creating a course as part of a Biomedical Engineering program.

Examining cultural structures and functions in biology

Scientific culture and structure organize biological sciences in many ways. We make choices concerning the systems and questions we study. Our research then amplifies these choices into factors that influence the directions of future research by shaping our hypotheses, data analyses, interpretation, publication venues, and dissemination via other methods. But our choices are shaped by more than objective curiosity-we are influenced by cultural paradigms reinforced by societal upbringing and scientific indoctrination during training. This extends to the systems and data that we consider to be ethically obtainable or available for study, and who is considered qualified to do research, ask questions, and communicate about research. It is also influenced by the profitability of concepts like open-access-a system designed to improve equity, but which enacts gatekeeping in unintended but foreseeable ways. Creating truly integrative biology programs will require more than intentionally developing departments or institutes that allow overlapping expertise in two or more subfields of biology. Interdisciplinary work requires the expertise of large and diverse teams of scientists working together-this is impossible without an authentic commitment to addressing, not denying, racism when practiced by individuals, institutions, and cultural aspects of academic science. We have identified starting points for remedying how our field has discouraged and caused harm, but we acknowledge there is a long path forward. This path must be paved with field-wide solutions and institutional buy-in: our solutions must match the scale of the problem. Together, we can integrate-not reintegrate-the nuances of biology into our field.

Network architecture and sex chromosome turnovers: Do epistatic interactions shape patterns of sex chromosome replacement?

Recent studies have revealed an astonishing diversity of sex chromosomes in many vertebrate lineages, prompting questions about the mechanisms of sex chromosome turnover. While there is considerable population genetic theory about the evolutionary forces promoting sex chromosome replacement, this theory has not yet been integrated with our understanding of the molecular and developmental genetics of sex determination. Here, we review recent data to examine four questions about how the structure of gene networks influences the evolution of sex determination. We argue that patterns of epistasis, arising from the structure of genetic networks, may play an important role in regulating the rates and patterns of sex chromosome replacement.

Theory of neuronal perturbome in cortical networks

Brains are composed of networks of neurons that are highly interconnected. A central question in neuroscience is how such neuronal networks operate in tandem to make a functioning brain. To understand this, we need to study how neurons interact with each other in action, such as when viewing a visual scene or performing a motor task. One way to approach this question is by perturbing the activity of functioning neurons and measuring the resulting influence on other neurons. By using computational models of neuronal networks, we studied how this influence in visual networks depends on connectivity. Our results help to interpret contradictory results from previous experimental studies and explain how different connectivity patterns can enhance information processing during natural vision.

To unravel the functional properties of the brain, we need to untangle how neurons interact with each other and coordinate in large-scale recurrent networks. One way to address this question is to measure the functional influence of individual neurons on each other by perturbing them in vivo. Application of such single-neuron perturbations in mouse visual cortex has recently revealed feature-specific suppression between excitatory neurons, despite the presence of highly specific excitatory connectivity, which was deemed to underlie feature-specific amplification. Here, we studied which connectivity profiles are consistent with these seemingly contradictory observations, by modeling the effect of single-neuron perturbations in large-scale neuronal networks. Our numerical simulations and mathematical analysis revealed that, contrary to the prima facie assumption, neither inhibition dominance nor broad inhibition alone were sufficient to explain the experimental findings; instead, strong and functionally specific excitatory–inhibitory connectivity was necessary, consistent with recent findings in the primary visual cortex of rodents. Such networks had a higher capacity to encode and decode natural images, and this was accompanied by the emergence of response gain nonlinearities at the population level. Our study provides a general computational framework to investigate how single-neuron perturbations are linked to cortical connectivity and sensory coding and paves the road to map the perturbome of neuronal networks in future studies.