Recent transcriptome data from yeast, worm, plants, and humans has shown that alternative polyadenylation (APA), a mechanism that enables expression of multiple 3′UTR isoforms for the same gene, is widespread in eukaryotic organisms. It is still poorly understood why metazoans require multiple 3′UTRs for the same gene, but accumulating evidence suggests that APA is largely regulated at a tissue-specific level. APA may direct combinatorial variation between cis-elements and microRNAs, perhaps to regulate gene expression in a tissue-specific manner. Apart from a few single gene anecdotes, this idea has not been systematically explored.
This dissertation research employs a systems biology approach to study the somatic tissue dynamics of APA and its impact on microRNA targeting networks in the small nematode C. elegans. In the first aim, tools were developed and applied to isolate and sequence mRNA from worm intestine and muscle tissues, which revealed pervasive tissue-specific APA correlated with microRNA regulation. The second aim provides genetic evidence that two worm genes use APA to escape repression by microRNAs in the body muscle. Finally, in aim three, mRNA from five additional somatic worm tissues was sequenced and their 3′ends mapped, allowing for an integrative study of APA and microRNA targeting dynamics in worms. Together, this work provides evidence that APA is a pervasive mechanism operating in somatic tissues of C. elegans with the potential to significantly rearrange their microRNA regulatory networks and precisely dose their gene expression.
This project utilized computational tools to analyze large data sets and interpreted the results from historical and philosophical perspectives. Tools deployed were derived from scientometrics, corpus linguistics, text-based analysis, network analysis, and GIS analysis to analyze more than 9000 articles (metadata and text) on systems biology. The application of these tools to a HPS project represents a novel approach.
The dissertation shows that systems biology has transitioned from a more mathematical, computational, and engineering-oriented discipline focusing on modeling to a more biology-oriented discipline that uses modeling as a means to address real biological problems. Also, the results show that bioengineering and medical research has increased within systems biology. This is reflected in the increase of the centrality of biology-related concepts such as cancer, over time. The dissertation also compares the development of systems biology in China with some other parts of the world, and reveals regional differences, such as a unique trajectory of systems biology in China related to a focus on traditional Chinese medicine.
This dissertation adds to the historiography of modern biology where few studies have focused on systems biology compared with the history of molecular biology and evolutionary biology.
The first chapter revisits some of the key experiments that contributed to the development of the repression model of genetic regulation in the lac operon and concludes that the early research on gene expression and genetic regulation depict an iterative and integrative process, which was neither reductionist nor holist. In doing so, it challenges a common application of a conceptual framework in the history of biology and offers an alternative framework. The second chapter argues that the concept of emergence in the history and philosophy of biology is too ambiguous to account for the current research in post-genomic molecular biology and it is often erroneously used to argue against some reductionist theses. The third chapter investigates the use of network representations of gene expression in developmental evolution research and takes up some of the conceptual and methodological problems it has generated. The concluding comments present potential avenues for future research arising from each substantial chapter.
In sum, this dissertation argues that the epistemic practices of gene expression research are an iterative and integrative process, which produces theoretical representations of the complex interactions in gene expression as networks. Moreover, conceptualizing these interactions as networks constrains empirical research strategies by the limited number of ways in which gene expression can be controlled through general rules of network interactions. Making these strategies explicit helps to clarify how they can explain the dynamic and adaptive features of genomes.
Pay-for-performance (PFP) is a relatively new approach to agricultural conservation that attaches an incentive payment to quantified reductions in nutrient runoff from a participating farm. Similar to a payment for ecosystem services approach, PFP lends itself to providing incentives for the most beneficial practices at the field level. To date, PFP conservation in the U.S. has only been applied in small pilot programs. Because monitoring conservation performance for each field enrolled in a program would be cost-prohibitive, field-level modeling can provide cost-effective estimates of anticipated improvements in nutrient runoff. We developed a PFP system that uses a unique application of one of the leading agricultural models, the USDA’s Soil and Water Assessment Tool, to evaluate the nutrient load reductions of potential farm practice changes based on field-level agronomic and management data. The initial phase of the project focused on simulating individual fields in the River Raisin watershed in southeastern Michigan. Here we present development of the modeling approach and results from the pilot year, 2015-2016. These results stress that (1) there is variability in practice effectiveness both within and between farms, and thus there is not one “best practice” for all farms, (2) conservation decisions are made most effectively at the scale of the farm field rather than the sub-watershed or watershed level, and (3) detailed, field-level management information is needed to accurately model and manage on-farm nutrient loadings.
Supplemental information mentioned in the article is attached as a separate document.
The emerging field of neuroprosthetics is focused on the development of new therapeutic interventions that will be able to restore some lost neural function by selective electrical stimulation or by harnessing activity recorded from populations of neurons. As more and more patients benefit from these approaches, the interest in neural interfaces has grown significantly and a new generation of penetrating microelectrode arrays are providing unprecedented access to the neurons of the central nervous system (CNS). These microelectrodes have active tip dimensions that are similar in size to neurons and because they penetrate the nervous system, they provide selective access to these cells (within a few microns). However, the very long-term viability of chronically implanted microelectrodes and the capability of recording the same spiking activity over long time periods still remain to be established and confirmed in human studies. Here we review the main responses to acute implantation of microelectrode arrays, and emphasize that it will become essential to control the neural tissue damage induced by these intracortical microelectrodes in order to achieve the high clinical potentials accompanying this technology.
In this study, a low-cycle fatigue experiment was conducted on printed wiring boards (PWB). The Weibull regression model and computational Bayesian analysis method were applied to analyze failure time data and to identify important factors that influence the PWB lifetime. The analysis shows that both shape parameter and scale parameter of Weibull distribution are affected by the supplier factor and preconditioning methods Based on the energy equivalence approach, a 6-cycle reflow precondition can be replaced by a 5-cycle IST precondition, thus the total testing time can be greatly reduced. This conclusion was validated by the likelihood ratio test of two datasets collected under two different preconditioning methods Therefore, the Weibull regression modeling approach is an effective approach for accounting for the variation of experimental setting in the PWB lifetime prediction.
Studies about the data quality of National Bridge Inventory (NBI) reveal missing, erroneous, and logically conflicting data. Existing data quality programs lack a focus on detecting the logical inconsistencies within NBI and between NBI and external data sources. For example, within NBI, the structural condition ratings of some bridges improve over a period while having no improvement activity or maintenance funds recorded in relevant attributes documented in NBI. An example of logical inconsistencies between NBI and external data sources is that some bridges are not located within 100 meters of any roads extracted from Google Map. Manual detection of such logical errors is tedious and error-prone. This paper proposes a systematical “hypothesis testing” approach for automatically detecting logical inconsistencies within NBI and between NBI and external data sources. Using this framework, the authors detected logical inconsistencies in the NBI data of two sample states for revealing suspicious data items in NBI. The results showed that about 1% of bridges were not located within 100 meters of any actual roads, and few bridges showed improvements in the structural evaluation without any reported maintenance records.
Quorum-sensing networks enable bacteria to sense and respond to chemical signals produced by neighboring bacteria. They are widespread: over 100 morphologically and genetically distinct species of eubacteria are known to use quorum sensing to control gene expression. This diversity suggests the potential to use natural protein variants to engineer parallel, input-specific, cell–cell communication pathways. However, only three distinct signaling pathways, Lux, Las, and Rhl, have been adapted for and broadly used in engineered systems. The paucity of unique quorum-sensing systems and their propensity for crosstalk limits the usefulness of our current quorum-sensing toolkit. This review discusses the need for more signaling pathways, roadblocks to using multiple pathways in parallel, and strategies for expanding the quorum-sensing toolbox for synthetic biology.