Biology subjects

Andre, D.

Publications and source records attributed to Andre, D..

3 recordsLinked to original sources

bioRxiv2026

Forecasting next-year change in antimicrobial resistance genes in Klebsiella pneumoniae and Acinetobacter baumannii from genomic surveillance data

Background: Surveillance tells laboratories which antimicrobial resistance genes are circulating now, but not which will change next. We built a model that forecasts, for each resistance gene and year, whether the following year brings a previously unseen allele (sequence variant), called emergence, or a change in the most common allele, called turnover. We tested it separately in Klebsiella pneumoniae and Acinetobacter baumannii. Results: We used genomes annotated with AMRFinderPlus: 2,385 gene-years across 331 genes for K.pneumoniae and 1,059 across 216 for A. baumannii. To remove the effect of sequencing effort, each gene-year was sampled to 10 records and the analysis repeated 25 times. Models were trained on earlier years and tested on later ones, and on genes held out of training. On later years every model ranked genes by risk better than simple baselines in both organisms, and results for held-out genes were close. In K.pneumoniae, turnover was predicted better than emergence (best area under the ROC curve, AUROC, 0.909 versus 0.819). In A. baumannii the order reversed (emergence 0.789, turnover 0.722). The two events also relied on different features. Emergence depended mainly on how many alleles a gene had already accumulated, in both organisms. Turnover in K. pneumoniae depended mainly on how dominant the leading allele already was, and a stability index added a small gain. In A. baumannii it was spread across many weaker features. There, 56% of changes in the leading allele involved only alleles already seen, against 23% in K. pneumoniae, which may make them harder to predict. Conclusions: Changes in resistance genes can be forecast a year ahead from routine genomic surveillance data, including for genes the model has not seen. How well it works, and what it depends on, differs between organisms, so models should be built and validated for each organism, not assumed to transfer. Such models could help laboratories decide which resistance genes to monitor most closely. Keywords: antimicrobial resistance; genomic surveillance; forecasting; machine learning; allele dynamics; Klebsiella pneumoniae; Acinetobacter baumannii

genomics↗

bioRxiv2021

GIGANTEA gene expression influence leaf senescence in Populus in two different ways

GIGANTEA (GI) genes have a central role in plant development and influence several processes such as light signaling, circadian rhythm and abiotic stress tolerance. Hybrid aspen T89 (Populus tremula x tremuloides) trees with low GI expression through RNAi have a severely compromised growth. In order to study the effect of reduced GI expression on leaf traits with special emphasis on leaf senescence, we grafted GI-RNAi scions onto wild type (WT) rootstocks and managed to restore scions growth. The RNAi line had distorted leaf shape and reduced photosynthesis, probably caused by modulating phloem or stomatal function, increased starch accumulation, higher carbon-to-nitrogen (C/N) ratio and a reduced capacity to withstand moderate light stress. GI-RNAi also induced senescence under long day (LD) and moderate light conditions. Furthermore, the GI-RNAi lines were affected in their capacity to respond to "autumn environmental cues" inducing senescence, a type of leaf senescence with characteristics different from senescence induced directly by stress under LD conditions. Whereas Overexpression of GI delayed senescence. The two different effects on leaf senescence were not affected by the expression of FT (Flowering locus T), were "local" - they followed the genotype of the branch independent on the position in the tree - and trees with modified gene expression grown in the field were affected in a similar way as under controlled conditions. Taken together, GI plays a central role to sense the environmental changes during autumn and determine the appropriate timing for leaf senescence in Populus. One sentence summaryLeaf senescence is a complex process that is not well understood, but this paper shows that changing the expression of one gene could influence leaf senescence in Populus trees in two separate ways.

plant biology↗

bioRxiv2018

Cell death in cells overlying lateral root primordia contributes to organ growth in Arabidopsis

Unlike animal development, plant organ growth is widely accepted to be determined by cell division without any contribution of cell elimination. We investigated this paradigm during Arabidopsis lateral root formation when growth of the new primordia (LRP) from pericycle-derived stem cells deep inside the root is reportedly facilitated by remodeling of the walls of overlying cells without apparent cell death. However, we observed the induction of marker genes for cell types undergoing developmental cell death in several cells overlying the growing LRP. Transmission electron microscopy, time-lapse confocal and light sheet microscopy techniques were used to establish that cell death occurred at least in a subset of endodermal LRP-overlying cells during organ emergence. Significantly, organ emergence was retarded in mutants lacking a positive cell death regulator, and restored by inducing cell death in cells overlying LRP. Hence, we conclude that in the case of LRP, cell elimination contributes to organ growth.

plant biology↗