Biology subjects

Chacon, M.

Publications and source records attributed to Chacon, M..

3 recordsLinked to original sources

bioRxiv2023

Degradation and bioconversion of complex municipal solid waste streams into human biotherapeutics and biopolymers

The use of biomass and organic waste as a feedstock for the production of fuels, chemicals and materials offers great potential to support the transition to net-zero and circular economic models. However, such renewable feedstocks are often complex, highly heterogeneous, and subject to geographical and seasonal variability, creating supply-chain inconsistency that impedes adoption. Towards addressing these challenges, the development of engineered microorganisms equipped with the ability to flexibly utilise complex, heterogenous substrate compositions for growth and bio-production would be greatly enabling. Here we show through careful strain selection and metabolic engineering, that Pseudomonas putida can be employed to permit efficient co-utilisation of highly heterogeneous substrate compositions derived from hydrolysed mixed municipal-like waste fractions, with remarkable resilience to compositional variability. To further illustrate this, one pot enzymatic pre-treatments of the five most abundant, hydrolytically labile, mixed waste feedstocks was performed - including food, plastic, organic, paper and cardboard, and textiles - for growth and synthesis of exemplar bio-products by engineered P. putida. Finally, prospective life cycle assessment and life cycle costing illustrated the climate change and economic advantage, respectively, of using the waste-derived feedstock for biomanufacturing compared to conventional waste treatment options. This work demonstrates the potential for expanding the treatment strategies for mixed municipal waste to include engineered microbial bio-production platforms that can accommodate variability in feedstock inputs to synthesise a range of chemical and material outputs.

synthetic biology↗

bioRxiv2022

Multiscale Entropy Analysis of Retinal Signals Reveals Reduced Complexity in a Mouse Model of Alzheimer's Disease

Alzheimers disease (AD) is one of the most significant health challenges of our time, affecting a growing number of the elderly population. In recent years, the retina has received increased attention as a candidate for AD biomarkers since it appears to manifest the pathological signatures of the disease. Therefore, its electrical activity may hint at AD-related physiological changes. However, it is unclear how AD affects retinal electrophysiology and what tools are more appropriate to detect these possible changes. In this study, we used entropy tools to estimate the complexity of the dynamics of healthy and diseased retinas at different ages. We recorded microelectroretinogram responses to visual stimuli of different nature from retinas of young and adult, wild-type and 5xFAD -an animal model of AD- mice. To estimate the complexity of signals, we used the multiscale entropy approach, which calculates the entropy at several time scales using a coarse graining procedure. We found that young retinas had more complex responses to different visual stimuli. Further, the responses of young, wild-type retinas to natural-like stimuli exhibited significantly higher complexity than young, 5xFAD retinas. Our findings support a theory of complexity-loss with aging and disease and can have significant implications for early AD diagnosis.

neuroscience↗

bioRxiv2021

Comparison of heat-inactivated and infectious SARS-CoV-2 across indoor surface materials shows comparable RT-qPCR viral signal intensity and persistence

Environmental monitoring in public spaces can be used to identify surfaces contaminated by persons with COVID-19 and inform appropriate infection mitigation responses. Research groups have reported detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) on surfaces days or weeks after the virus has been deposited, making it difficult to estimate when an infected individual may have shed virus onto a SARS-CoV-2 positive surface, which in turn complicates the process of establishing effective quarantine measures. In this study, we determined that reverse transcription-quantitative polymerase chain reaction (RT-qPCR) detection of viral RNA from heat-inactivated particles experiences minimal decay over seven days of monitoring on eight out of nine surfaces tested. The properties of the studied surfaces result in RT-qPCR signatures that can be segregated into two material categories, rough and smooth, where smooth surfaces have a lower limit of detection. RT-qPCR signal intensity (average quantification cycle (Cq)) can be correlated to surface viral load using only one linear regression model per material category. The same experiment was performed with infectious viral particles on one surface from each category, with essentially identical results. The stability of RT-qPCR viral signal demonstrates the need to clean monitored surfaces after sampling to establish temporal resolution. Additionally, these findings can be used to minimize the number of materials and time points tested and allow for the use of heat-inactivated viral particles when optimizing environmental monitoring methods. ImportanceEnvironmental monitoring is an important tool for public health surveillance, particularly in settings with low rates of diagnostic testing. Time between sampling public environments, such as hospitals or schools, and notifying stakeholders of the results should be minimal, allowing decisions to be made towards containing outbreaks of coronavirus disease 2019 (COVID-19). The Safer At School Early Alert program (SASEA) [1], a large-scale environmental monitoring effort in elementary school and child care settings, has processed > 13,000 surface samples for SARS-CoV-2, detecting viral signals from 574 samples. However, consecutive detection events necessitated the present study to establish appropriate response practices around persistent viral signals on classroom surfaces. Other research groups and clinical labs developing environmental monitoring methods may need to establish their own correlation between RT - qPCR results and viral load, but this work provides evidence justifying simplified experimental designs, like reduced testing materials and the use of heat-inactivated viral particles.

microbiology↗