Export of functional Streptomyces coelicolor alditol oxidase to the periplasm or cell surface of Escherichia coli and its application in whole-cell biocatalysis

Streptomyces coelicolor A3(2) alditol oxidase (AldO) is a soluble monomeric flavoprotein in which the flavin cofactor is covalently linked to the polypeptide chain. AldO displays high reactivity towards different polyols such as xylitol and sorbitol. These characteristics make AldO industrially relevant, but full biotechnological exploitation of this enzyme is at present restricted by laborious and costly purification steps. To eliminate the need for enzyme purification, this study describes a whole-cell AldO biocatalyst system. To this end, we have directed AldO to the periplasm or cell surface of Escherichia coli. For periplasmic export, AldO was fused to endogenous E. coli signal sequences known to direct their passenger proteins into the SecB, signal recognition particle (SRP), or Twin-arginine translocation (Tat) pathway. In addition, AldO was fused to an ice nucleation protein (INP)-based anchoring motif for surface display. The results show that Tat-exported AldO and INP-surface-displayed AldO are active. The Tat-based system was successfully employed in converting xylitol by whole cells, whereas the use of the INP-based system was most likely restricted by lipopolysaccharide LPS in wild-type cells. It is anticipated that these whole-cell systems will be a valuable tool for further biological and industrial exploitation of AldO and other cofactor-containing enzymes.

The power of model-to-crop translation illustrated by reducing seed loss from pod shatter in oilseed rape

Key message: Elucidation of key regulators in Arabidopsis fruit patterning has facilitated knowledge-translation into crop species to address yield loss caused by premature seed dispersal (pod shatter). Abstract: In the 1980s, plant scientists descended on a small weed Arabidopsis thaliana (thale cress) and developed it into a powerful model system to study plant biology. The massive advances in genetics and genomics since then have allowed us to obtain incredibly detailed knowledge on specific biological processes of Arabidopsis growth and development, its genome sequence and the function of many of the individual genes. This wealth of information provides immense potential for translation into crops to improve their performance and address issues of global importance such as food security. Here, we describe how fundamental insight into the genetic mechanism by which seed dispersal occurs in members of the Brassicaceae family can be exploited to reduce seed loss in oilseed rape (Brassica napus). We demonstrate that by exploiting data on gene function in model species, it is possible to adjust the pod-opening process in oilseed rape, thereby significantly increasing yield. Specifically, we identified mutations in multiple paralogues of the INDEHISCENT and GA4 genes in B. napus and have overcome genetic redundancy by combining mutant alleles. Finally, we present novel software for the analysis of pod shatter data that is applicable to any crop for which seed dispersal is a serious problem. These findings highlight the tremendous potential of fundamental research in guiding strategies for crop improvement

Smart Mat for Respiratory Activity Detection: Study in a Clinical Setting

We discuss in this paper a study of a smart and unobtrusive mattress in a clinical setting on a population with cardiorespiratory problems. Up to recently, the vast majority of studies with unobtrusive sensors are done with healthy populations. The unobtrusive monitoring of the Respiratory Rate (RR) is essential for proposing better diagnoses. Thus, new industrial and research activity on smart mattresses is targeting respiratory rate in an Internet-of-Things (IoT) context. In our work, we are interested in the performances of a microbend fiber optic sensor (FOS) mattress on 81 subjects admitted in the Cardiac Intensive Care Unit (CICU) by estimating the RR from their ballistocardiograms (BCG). Our study proposes a new RR estimator, based on harmonic plus noise models (HNM) and compares it with known estimators such as MODWT and CLIE. The goal is to examine, using a more representative and bigger dataset, the performances of these methods and of the smart mattress in general. Results of applying these three estimators on the BCG show that MODWT is more accurate with an average mean absolute error (MAE) of 1.97 ± 2.12 BPM. However, the HNM estimator has space for improvements with estimation errors of 2.91 ± 4.07 BPM. The smart mattress works well within a standard RR range of 10–20 breaths-per-minute (BPM) but gets less accurate with a bigger range of estimation. These results highlight the need to test these sensors in much more realistic contexts

Holding-on: co-evolution between infant carrying and grasping behaviour in strepsirrhines

The origin and evolution of manual grasping remain poorly understood. The ability to cling requires important grasping abilities and is essential to survive in species where the young are carried in the fur. A previous study has suggested that this behaviour could be a pre-adaptation for the evolution of fine manipulative skills. In this study we tested the co-evolution between infant carrying in the fur and manual grasping abilities in the context of food manipulation. As strepsirrhines vary in the way infants are carried (mouth vs. fur), they are an excellent model to test this hypothesis. Data on food manipulation behaviour were collected for 21 species of strepsirrhines. Our results show that furcarrying species exhibited significantly more frequent manual grasping of food items. This study clearly illustrates the potential novel insights that a behaviour (infant carrying) that has previously been largely ignored in the discussion of the evolution of primate manipulation can bring.peerReviewe