Planetary mass spectrometry for agnostic life detection in the Solar system

For the past fifty years of space exploration, mass spectrometry has provided unique chemical and physical insights on the characteristics of other planetary bodies in the Solar System. A variety of mass spectrometer types, including magnetic sector, quadrupole, time-of-flight, and ion trap, have and will continue to deepen our understanding of the formation and evolution of exploration targets like the surfaces and atmospheres of planets and their moons. An important impetus for the continuing exploration of Mars, Europa, Enceladus, Titan, and Venus involves assessing the habitability of solar system bodies and, ultimately, the search for life—a monumental effort that can be advanced by mass spectrometry. Modern flight-capable mass spectrometers, in combination with various sample processing, separation, and ionization techniques enable sensitive detection of chemical biosignatures. While our canonical knowledge of biosignatures is rooted in Terran-based examples, agnostic approaches in astrobiology can cast a wider net, to search for signs of life that may not be based on Terran-like biochemistry. Here, we delve into the search for extraterrestrial chemical and morphological biosignatures and examine several possible approaches to agnostic life detection using mass spectrometry. We discuss how future missions can help ensure that our search strategies are inclusive of unfamiliar life forms.https://www.frontiersin.org/articles/10.3389/fspas.2021.755100/ful

Experimental Evolution of an Oncolytic Vesicular Stomatitis Virus with Increased Selectivity for p53-Deficient Cells

Experimental evolution has been used for various biotechnological applications including protein and microbial cell engineering, but less commonly in the field of oncolytic virotherapy. Here, we sought to adapt a rapidly evolving RNA virus to cells deficient for the tumor suppressor gene p53, a hallmark of cancer cells. To achieve this goal, we established four independent evolution lines of the vesicular stomatitis virus (VSV) in p53-knockout mouse embryonic fibroblasts (p53−/− MEFs) under conditions favoring the action of natural selection. We found that some evolved viruses showed increased fitness and cytotoxicity in p53−/− cells but not in isogenic p53+/+ cells, indicating gene-specific adaptation. However, full-length sequencing revealed no obvious or previously described genetic changes associated with oncolytic activity. Half-maximal effective dose (EC50) assays in mouse p53-positive colon cancer (CT26) and p53-deficient breast cancer (4T1) cells indicated that the evolved viruses were more effective against 4T1 cells than the parental virus or a reference oncolytic VSV (MΔ51), but showed no increased efficacy against CT26 cells. In vivo assays using 4T1 syngeneic tumor models showed that one of the evolved lines significantly delayed tumor growth compared to mice treated with the parental virus or untreated controls, and was able to induce transient tumor suppression. Our results show that RNA viruses can be specifically adapted typical cancer features such as p53 inactivation, and illustrate the usefulness of experimental evolution for oncolytic virotherapy

Dengue Virus Capsid Protein Usurps Lipid Droplets for Viral Particle Formation

Dengue virus is responsible for the highest rates of disease and mortality among the members of the Flavivirus genus. Dengue epidemics are still occurring around the world, indicating an urgent need of prophylactic vaccines and antivirals. In recent years, a great deal has been learned about the mechanisms of dengue virus genome amplification. However, little is known about the process by which the capsid protein recruits the viral genome during encapsidation. Here, we found that the mature capsid protein in the cytoplasm of dengue virus infected cells accumulates on the surface of ER-derived organelles named lipid droplets. Mutagenesis analysis using infectious dengue virus clones has identified specific hydrophobic amino acids, located in the center of the capsid protein, as key elements for lipid droplet association. Substitutions of amino acid L50 or L54 in the capsid protein disrupted lipid droplet targeting and impaired viral particle formation. We also report that dengue virus infection increases the number of lipid droplets per cell, suggesting a link between lipid droplet metabolism and viral replication. In this regard, we found that pharmacological manipulation of the amount of lipid droplets in the cell can be a means to control dengue virus replication. In addition, we developed a novel genetic system to dissociate cis-acting RNA replication elements from the capsid coding sequence. Using this system, we found that mislocalization of a mutated capsid protein decreased viral RNA amplification. We propose that lipid droplets play multiple roles during the viral life cycle; they could sequester the viral capsid protein early during infection and provide a scaffold for genome encapsidation

RNA delivery by extracellular vesicles in mammalian cells and its applications.

The term 'extracellular vesicles' refers to a heterogeneous population of vesicular bodies of cellular origin that derive either from the endosomal compartment (exosomes) or as a result of shedding from the plasma membrane (microvesicles, oncosomes and apoptotic bodies). Extracellular vesicles carry a variety of cargo, including RNAs, proteins, lipids and DNA, which can be taken up by other cells, both in the direct vicinity of the source cell and at distant sites in the body via biofluids, and elicit a variety of phenotypic responses. Owing to their unique biology and roles in cell-cell communication, extracellular vesicles have attracted strong interest, which is further enhanced by their potential clinical utility. Because extracellular vesicles derive their cargo from the contents of the cells that produce them, they are attractive sources of biomarkers for a variety of diseases. Furthermore, studies demonstrating phenotypic effects of specific extracellular vesicle-associated cargo on target cells have stoked interest in extracellular vesicles as therapeutic vehicles. There is particularly strong evidence that the RNA cargo of extracellular vesicles can alter recipient cell gene expression and function. During the past decade, extracellular vesicles and their RNA cargo have become better defined, but many aspects of extracellular vesicle biology remain to be elucidated. These include selective cargo loading resulting in substantial differences between the composition of extracellular vesicles and source cells; heterogeneity in extracellular vesicle size and composition; and undefined mechanisms for the uptake of extracellular vesicles into recipient cells and the fates of their cargo. Further progress in unravelling the basic mechanisms of extracellular vesicle biogenesis, transport, and cargo delivery and function is needed for successful clinical implementation. This Review focuses on the current state of knowledge pertaining to packaging, transport and function of RNAs in extracellular vesicles and outlines the progress made thus far towards their clinical applications

Robust reconstruction for CS-based fetal beats detection

ABSTRACT Due to its possible low-power implementation, Compressed Sensing (CS) is an attractive tool for physiological signal acquisition in emerging scenarios like Wireless Body Sensor Networks (WBSN) and telemonitoring applications. In this work we consider the continuous monitoring and analysis of the fetal ECG signal (fECG). We propose a modification of the low-complexity CS reconstruction SL0 algorithm, improving its robustness in the presence of noisy original signals and possibly ill-conditioned sensing/reconstruction procedures. We show that, while maintaining the same computational cost of the original algorithm, the proposed modification significantly improves the reconstruction quality, both for synthetic and real-world ECG signals. We also show that the proposed algorithm allows robust heart beat classification when sparse matrices, implementable with very low computational complexity, are used for compressed sensing of the ECG signal

Concentration dependence of the subunit association of oligomers and viruses and the modification of the latter by urea binding.

A theoretical model is presented that accounts for the facilitation of the pressure dissociation of R17 phage, and for the partial restoration of the concentration dependence of the dissociation, by the presence of subdenaturing concentrations of urea. As an indifferent osmolyte urea should promote the stability of the protein aggregates under pressure, and the decrease in pressure stability with urea concentration demonstrates that such indirect solvent effects are not significant for this case, and that the progressive destabilization is the result of direct protein-urea interactions. By acting as a "homogenizer" of the properties of the phage particles, urea addition converts the pressure-induced deterministic dissociation of the phage into a limited stochastic equilibrium. The model establishes the origin of the uniform progression from the stochastic equilibrium of dimers, to the temperature-dependent and partially concentration-dependent association of tetramers, to the fully deterministic equilibrium observed in many multimers and in the virus capsids

A low-complexity photoplethysmographic systolic peak detector for compressed sensed data

Objective: Recent advances in wearable technologies and signal processing have made it possible to perform health monitoring during everyday life activities. Despite the fact that new technologies allow the storage of large volumes of data on small devices, limitations remain when data have to be transmitted or processed with devices with both energy and computational constraints. Approach: This work focuses on the implementation and validation of a photoplethysmogram (PPG) low- complexity analysis method for sensors that acquire a compressed PPG signal through Compressive Sensing (CS) and allows for the accurate detection of the PPG systolic peak in the compressed domain. Three public datasets were used consisting of a total of about 52 hours of PPG signals from 600 patients with normal and abnormal rhythms. Peaks were manually annotated by experts or derived from the annotated synchronized ECG. Main Results: The proposed method achieved a pooled average F1 measure on the three datasets of 91\ub18% for a 5% compression ratio (CR), 89\ub110% for CR=70% and 82\ub112% for CR of 90%. The pooled average F1 measure on the original uncompressed data using an offline open source peak detector is F1 = 91\ub111%. The proposed method is up to 3c100 times faster with respect to methods using decompression followed by peak detection. Significance: Results demonstrate that it is possible to achieve detection performance, in terms of the F1 measure, comparable with those obtained on the original uncompressed and filtered signal, making the proposed approach appropriate for real-time wearable systems with energy and computation constraints

Atrial fibrillation detection on compressed sensed ECG

Objective: Compressive sensing (CS) approaches to electrocardiogram (ECG) analysis provide efficient methods for real time encoding of cardiac activity. In doing so, it is important to assess the downstream effect of the compression on any signal processing and classification algorithms. CS is particularly suitable for low power wearable devices, thanks to its low-complex digital or hardware implementation that directly acquires a compressed version of the signal through random projections. In this work, we evaluate the impact of CS compression on atrial fibrillation (AF) detection accuracy. Approach: We compare schemes with data reconstruction based on wavelet and Gaussian models, followed by a P&T-based identification of beat-to-beat (RR) intervals on the MIT-BIH atrial fibrillation database. A state-of-the-art AF detector is applied to the RR time series and the accuracy of the AF detector is then evaluated under different levels of compression. We also consider a new beat detection procedure which operates directly in the compressed domain, avoiding costly signal reconstruction procedures. Main results: We demonstrate that for compression ratios up to 30$$ the AF detector applied to RR intervals derived from the compressed signal exhibits results comparable to those achieved when employing a standard QRS detector on the raw uncompressed signals, and exhibits only a 2% accuracy drop at a compression ratio of 60%. We also show that the Gaussian-based reconstruction approach is superior in terms of AF detection accuracy, with a negligible drop in performance at a compression ratio\u2009\u2009 6475%, compared to a wavelet approach, which exhibited a significant drop in accuracy at a compression ratio\u2009\u2009 6565%. Significance: The results suggest that CS should be considered as a plausible methodology for both efficient real time ECG compression (at moderate compression rates) and for offline analysis (at high compression rates)

A study on the origins of studetns misconceptions about energy-yielding metabolism

Abstract of the panel presented at the SBBq annual meeting (see attachament)

Matched filtering for heart rate estimation on compressive sensing ECG measurements

Objective: Compressive Sensing (CS) has recently been applied as a low complexity compression framework for long-term monitoring of electrocardiogram signals using Wireless Body Sensor Networks. Long-term recording of ECG signals can be useful for diagnostic purposes and to monitor the evolution of several widespread diseases. In particular, beat to beat intervals provide important clinical information, and these can be derived from the ECG signal by computing the distance between QRS complexes (R-peaks). Numerous methods for R- peak detection are available for uncompressed ECG. However, in case of compressed sensed data, signal reconstruction can be performed with relatively complex optimisation algorithms, which may require significant energy consumption. This article addresses the problem of hearth rate estimation from com- pressive sensing electrocardiogram (ECG) recordings, avoiding the reconstruction of the entire signal. Methods: We consider a framework where the ECG signals are represented under the form of CS linear measurements. The QRS locations are estimated in the compressed domain by computing the correlation of the compressed ECG and a known QRS template. Results: Experiments on actual ECG signals show that our novel solution is competitive with methods applied to the reconstructed signals. Conclusion: Avoiding the reconstruction procedure, the proposed method proves to be very convenient for real-time, low-power applications