Enabling Experimental Evolution: Multi-Parameter Sensor System Integration into a Culture/Stressor Biofluidics System

Experimental evolution (EE) exposes microbial communities to ecological stressors, simulating dynamics up to near-extinction events. Combined with comparative sequencing and other molecular tools, such data can inform the genetic and other biological mechanisms underlying extremophile adaptation, and other observed effects. Automating this type of experiment using biofluidics can mitigate many traditional obstacles, including delays in assay results and environment adjustment and the need for many replicates. A first-generation device for automating EE procedures, the Automated Adaptive Directed Evolution Chamber (AADEC), was developed at NASA Ames. UV-C radiation was the stressor, an LED-photodiode array measured optical density, magnetic agitation and peristaltic pump systems ensured nutrient availability, and Arduino microcontrollers provided control. Escherichia coli in LB kanamycin media was used for testing and performance verification. A manual laboratory procedure with timed exposure to UV-C was performed to typify tolerance acquisition. Approximately a 106 factor increase in survival ratio was recorded over multiple iterations. Currently, a second-generation device is being developed integrating more real-time sensors: redox potential (ORP), indicating available/consumed metabolic energy; dissolved oxygen (DO), indicating aerobic/anaerobic growth; pH, indicating metabolic products; and electrical conductivity (EC), another indicator of metabolic products. The EC sensor system was constructed and calibrated in-house and matched commercial sensors in the required range. A Raspberry Pi computer automated the electrical system, allowing real-time data acquisition. The fluidics card was made of CNC-milled polycarbonate for biocompatibility. Each sensor parameter can also be used as a selection pressure alone or in combination with others to create extreme microbial environments. As a proof of concept, this work demonstrated sensor operation in one pair of growth-sensor chambers. It can be expanded to a multi-chamber system to enable inter-culture comparisons and multi-population studies. The prior Arduino system will be ported to the RPi system. Future stressors to be added include thermal, reactive oxygen species, and varying nutrient availability

Employing Automated Experimental Evolution to Understand Survival Strategies of Lab-Grown Extremophiles

Experimental evolution (EE) exposes microbes to intentional stressors to improve resistance through artificial mutation. The resulting changes to metabolic pathways, protein structure, and genetic sequences, along with traditional genetic engineering tools, to can help understand the mechanisms of improved tolerance. An automated experimental set-up -- the Automated Adaptive Directed Evolution Chamber (AADEC) -- with minimal scope for human interference was developed at NASA Ames. A second- generation device integrating more real-time biochemical sensors has been developed recently. Added sensors include pH for indicating metabolic products, oxidation-reduction potential (ORP) for indicating available/consumed metabolic energy, dissolved oxygen (DO) for indicating aerobic/anaerobic growth cycles, and electrical conductivity (EC) as an additional indicator of metabolic products. With four additional sensors, the system is biochemically more informative in real-time. More importantly, each sensor parameter can be used as a selection pressure, individually or in combination with others, to artificially create and control inhospitable environments analogous to extremophile habitats for microbial growth in the lab. Potential stressors to be added in the future include thermal, reactive oxygen species, metal-ion concentrations, and varying nutrient availability

Entrepreneurial Behaviour of the Agriculture Students-A review

The present study aimed to investigate the factors that influence the entrepreneurial behavior of college students. The study identified various personal and situational factors that may affect entrepreneurial behavior. The results showed that personality traits, such as openness, extraversion, and conscientiousness, had a significant positive impact on entrepreneurial behavior. Specific motivational traits, such as entrepreneurial self-efficacy, internal locus of control, and risk-taking propensity, were also significant predictors of entrepreneurial behavior. Situational factors, such as entrepreneurship education, were found to have a significant positive impact on entrepreneurial behavior, with entrepreneurial self-efficacy playing a key mediating role in this relationship. Attitudes towards entrepreneurship were found to be a significant driver of entrepreneurial intention, with perceived desirability and feasibility, as well as perceived individual and collective efficacy, also significant predictors of entrepreneurial intention. Sustainable entrepreneurial intention was found to be influenced by attitude towards the behavior variable, with subjective norms playing an indirect role in mediating this effect. Overall, the study suggests that personal traits, such as personality and motivational factors, as well as situational factors, such as education and attitudes towards entrepreneurship, are significant predictors of entrepreneurial behavior. These findings have important implications for educators and policymakers who seek to promote entrepreneurial behavior among college students. Future research should continue to explore the complex relationships between personal and situational factors and entrepreneurial behavior to further enhance our understanding of this important phenomenon. &nbsp

Looking for life in the icy crust of Europa

Presented at the Georgia Tech Career, Research, and Innovation Development Conference (CRIDC).Jupiter’s icy moon Europa is of great scientific interest due to its potential for harboring extraterrestrial life. Rather than directly looking for microbial life using optical microscopes and limiting ourselves to life as we know it on Earth, looking for chemical biosignatures is a more holistic approach to search for life. Biosignatures are chemical marks left behind by life systems indicating their presence. For instance, all life on Earth has amino acids as its building blocks and as genetic information storage packets. Similarly, life on Earth seems to be favored by only one type of salts – chloride. Finding biogenic amino acids and chloride salts in the right levels on Europa could be encouraging. To detect amino acids and salts on Europa, we are developing an in-situ sampler, the Icy Moon Penetrator Organic Analyzer (IMPOA), a coke can-sized device. IMPOA is currently capable of sustaining 55,000 G impact force, penetrates deep into the ice crust, collects samples, and analyzes them. IMPOA uses an optical set up to detect the fluorescence of laser-activated amino acids and an embedded contactless electrochemical conductivity sensor for salt detection

Future of the Search for Life: Workshop Report

International audienceThe 2-week, virtual Future of the Search for Life science and engineering workshop brought together more than 100 scientists, engineers, and technologists in March and April 2022 to provide their expert opinion on the interconnections between life-detection science and technology. Participants identified the advances in measurement and sampling technologies they believed to be necessary to perform in situ searches for life elsewhere in our Solar System, 20 years or more in the future. Among suggested measurements for these searches, those pertaining to three potential indicators of life termed “dynamic disequilibrium,” “catalysis,” and “informational polymers” were identified as particularly promising avenues for further exploration. For these three indicators, small breakout groups of participants identified measurement needs and knowledge gaps, along with corresponding constraints on sample handling (acquisition and processing) approaches for a variety of environments on Enceladus, Europa, Mars, and Titan. Despite the diversity of these environments, sample processing approaches all tend to be more complex than those that have been implemented on missions or envisioned for mission concepts to date. The approaches considered by workshop breakout groups progress from nondestructive to destructive measurement techniques, and most involve the need for fluid (especially liquid) sample processing. Sample processing needs were identified as technology gaps. These gaps include technology and associated sampling strategies that allow the preservation of the thermal, mechanical, and chemical integrity of the samples upon acquisition; and to optimize the sample information obtained by operating suites of instruments on common samples. Crucially, the interplay between science-driven life-detection strategies and their technological implementation highlights the need for an unprecedented level of payload integration and extensive collaboration between scientists and engineers, starting from concept formulation through mission deployment of life-detection instruments and sample processing systems

Community Report from the Biosignatures Standards of Evidence Workshop

The search for life beyond the Earth is the overarching goal of the NASA Astrobiology Program, and it underpins the science of missions that explore the environments of Solar System planets and exoplanets. However, the detection of extraterrestrial life, in our Solar System and beyond, is sufficiently challenging that it is likely that multiple measurements and approaches, spanning disciplines and missions, will be needed to make a convincing claim. Life detection will therefore not be an instantaneous process, and it is unlikely to be unambiguous-yet it is a high-stakes scientific achievement that will garner an enormous amount of public interest. Current and upcoming research efforts and missions aimed at detecting past and extant life could be supported by a consensus framework to plan for, assess and discuss life detection claims (c.f. Green et al., 2021). Such a framework could help increase the robustness of biosignature detection and interpretation, and improve communication with the scientific community and the public. In response to this need, and the call to the community to develop a confidence scale for standards of evidence for biosignature detection (Green et al., 2021), a community-organized workshop was held on July 19-22, 2021. The meeting was designed in a fully virtual (flipped) format. Preparatory materials including readings, instructional videos and activities were made available prior to the workshop, allowing the workshop schedule to be fully dedicated to active community discussion and prompted writing sessions. To maximize global interaction, the discussion components of the workshop were held during business hours in three different time zones, Asia/Pacific, European and US, with daily information hand-off between group organizers

3rd National Conference on Image Processing, Computing, Communication, Networking and Data Analytics

This volume contains contributed articles presented in the conference NCICCNDA 2018, organized by the Department of Computer Science and Engineering, GSSS Institute of Engineering and Technology for Women, Mysore, Karnataka (India) on 28th April 2018