The circadian clock-associated small GTPase LIGHT INSENSITIVE PERIOD1 suppresses light-controlled endoreplication and affects tolerance to salt stress in Arabidopsis

Emerging role of small GTPases and their interactome in plants to combat abiotic and biotic stress

Plants are frequently subjected to abiotic and biotic stress which causes major impediments in their growth and development. It is emerging that small guanosine triphosphatases (small GTPases), also known as monomeric GTP-binding proteins, assist plants in managing environmental stress. Small GTPases function as tightly regulated molecular switches that get activated with the aid of guanosine triphosphate (GTP) and deactivated by the subsequent hydrolysis of GTP to guanosine diphosphate (GDP). All small GTPases except Rat sarcoma (Ras) are found in plants, including Ras-like in brain (Rab), Rho of plant (Rop), ADP-ribosylation factor (Arf) and Ras-like nuclear (Ran). The members of small GTPases in plants interact with several downstream effectors to counteract the negative effects of environmental stress and disease-causing pathogens. In this review, we describe processes of stress alleviation by developing pathways involving several small GTPases and their associated proteins which are important for neutralizing fungal infections, stomatal regulation, and activation of abiotic stress-tolerant genes in plants. Previous reviews on small GTPases in plants were primarily focused on Rab GTPases, abiotic stress, and membrane trafficking, whereas this review seeks to improve our understanding of the role of all small GTPases in plants as well as their interactome in regulating mechanisms to combat abiotic and biotic stress. This review brings to the attention of scientists recent research on small GTPases so that they can employ genome editing tools to precisely engineer economically important plants through the overexpression/knock-out/knock-in of stress-related small GTPase genes.

Interpreting machine learning models to investigate circadian regulation and facilitate exploration of clock function

The circadian clock is an internal molecular 24-h timer that is critical to life on Earth. We describe a series of artificial intelligence (AI)– and machine learning (ML)–based approaches that enable more cost-effective analysis and insight into circadian regulation and function. Throughout the manuscript, we illuminate what is inside the ML “black box” via explanation or interpretation of predictive ML models. Using this interpretation of our models, we derive biological insights into why a prediction was made, alongside accurate predictions. Most innovatively, we use only DNA sequence features for accurate circadian gene expression prediction. Using explainable AI, we define possible, responsible regulatory elements as we make these predictions; this critically requires no prior knowledge of regulatory elements.

The circadian clock is an important adaptation to life on Earth. Here, we use machine learning to predict complex, temporal, and circadian gene expression patterns in Arabidopsis. Most significantly, we classify circadian genes using DNA sequence features generated de novo from public, genomic resources, facilitating downstream application of our methods with no experimental work or prior knowledge needed. We use local model explanation that is transcript specific to rank DNA sequence features, providing a detailed profile of the potential circadian regulatory mechanisms for each transcript. Furthermore, we can discriminate the temporal phase of transcript expression using the local, explanation-derived, and ranked DNA sequence features, revealing hidden subclasses within the circadian class. Model interpretation/explanation provides the backbone of our methodological advances, giving insight into biological processes and experimental design. Next, we use model interpretation to optimize sampling strategies when we predict circadian transcripts using reduced numbers of transcriptomic timepoints. Finally, we predict the circadian time from a single, transcriptomic timepoint, deriving marker transcripts that are most impactful for accurate prediction; this could facilitate the identification of altered clock function from existing datasets.

The perennial clock is an essential timer for seasonal growth events and cold hardiness

Over the last several decades, changes in global temperatures have led to changes in local environments affecting the growth conditions for many species. This is a trend that makes it even more important to understand how plants respond to local variations and seasonal changes in climate. To detect daily and seasonal changes as well as acute stress factors such as cold and drought, plants rely on a circadian clock. This chapter introduces the current knowledge and literature about the setup and function of the circadian clock in various tree and perennial species, with a focus on the Populus genus.

The Legionella pneumophila kai operon is implicated in stress response and confers fitness in competitive environments

Legionella pneumophila uses aquatic protozoa as replication niche and protection from harsh environments. Although L. pneumophila is not known to have a circadian clock, it encodes homologues of the KaiBC proteins of Cyanobacteria that regulate circadian gene expression. We show that L. pneumophila kaiB, kaiC and the downstream gene lpp1114, are transcribed as a unit under the control of the stress sigma factor RpoS. KaiC and KaiB of L. pneumophila do not interact as evidenced by yeast and bacterial two-hybrid analyses. Fusion of the C-terminal residues of cyanobacterial KaiB to Legionella KaiB restores their interaction. In contrast, KaiC of L. pneumophila conserved autophosphorylation activity, but KaiB does not trigger the dephosphorylation of KaiC like in Cyanobacteria. The crystal structure of L. pneumophila KaiB suggests that it is an oxidoreductase-like protein with a typical thioredoxin fold. Indeed, mutant analyses revealed that the kai operon-encoded proteins increase fitness of L. pneumophila in competitive environments, and confer higher resistance to oxidative and sodium stress. The phylogenetic analysis indicates that L. pneumophila KaiBC resemble Synechosystis KaiC2B2 and not circadian KaiB1C1. Thus, the L. pneumophila Kai proteins do not encode a circadian clock, but enhance stress resistance and adaption to changes in the environments.