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Evolutionary trajectory of pattern recognition receptors in plants

Plant cell-surface receptors that are known to participate in immunity, development, and reproductive processes include the LRR-, G-lectin-, Wall-associated kinase (WAK)-, Domain of Unknown Function 26 (Duf26)-, L-lectin-, Lysin motif (LysM)-, and Malectin-containing RLKs and RLPs (Fig. 1a–h). There are additional RLK families with different ectodomains, such as the proline-rich extensin-like receptor kinases (PERKs) and thaumatin-like protein kinases (TLPKs)9,13. However, their function in immunity is not well-characterized. Cell-surface receptors with LRR-, G-lectin-, WAK-, and LysM-ectodomains have been reported to recognise PAMPs, while others perceive self-molecules or unidentified ligands (Fig. 1h; Supplementary Fig. 1). Recognition of the diverse array of ligands is likely to be accomplished by variable structures and combinations of different ectodomains (Fig. 1a–g). To trace the origins of different receptor classes within the plant lineage, we first identified RLKs and RLPs in 350 genomes from Glaucophyta, red algae, green algae, Bryophytes, and Tracheophytes. We define here RLKs as any proteins with both 1–2 TMs and KDs, and RLPs as any protein with 1–2 TMs, but lack KDs. In total, we identified 177,645 RLKs, almost up to 70% of which possess either LRR-, G-lectin-, WAK-, Duf26-, L-lectin-, LysM-and Malectin-ectodomains (Fig. 1i). Next, we searched for proteins with these ectodomains and TMs that lack KDs and found 41,144 RLPs (Fig. 1j). We further examined which of the identified RLKs and RLPs families are likely to be involved in immunity. A previous report suggested a positive correlation between the gene family sizes of cell-surface immune receptors and intracellular immune receptors (the NB-ARC family) across the angiosperms4. We examined the correlation between the relative size (%; number of identified genes in the family/numbers of searched genes × 100; see methods) of the RLK families, the RLPs families, and the NB-ARC family in each genome. Notably, most RLK families (except for the LysM-RLKs) exhibit positive correlations with the NB-ARC family, while most RLP families (except for the LRR-RLPs) do not exhibit positive correlation with the NB-ARC family (Main Fig. 1k). Furthermore, we checked the expression level of these receptor families in Arabidopsis thaliana during immunity. Notably, the RLKs, except for LRR-and Malectin-RLKs, generally exhibit higher expression levels compared to the RLPs during immunity (Main Fig. 1k; Supplementary Fig. 2). These data collectively suggest that the RLKs are more likely to be involved in immunity than the RLPs.

Next, we examined the presence or absence of ectodomains (LRR-, G-lectin-, WAK-, Duf26-, L-lectin-, LysM-and Malectin-ectodomains lacking TM or KD; ectodomain-only proteins), RLPs (TM-bound ectodomains) and RLKs (ectodomains encompassing both TM and KD) in the plant lineage (Fig. 2; Supplementary Fig. 3; Supplementary Data 1a–c). Ectodomains exhibit an ancient heritage, with LRR-, WAK-, LysM-, Malectin-, and L-lectin-domains dating back to the era of Glaucophyta. Similarly, relatively ancient counterparts such as LRR-RLPs, WAK-RLPs, LysM-RLPs, Malectin-RLPs, and L-lectin-RLPs are found in both Glaucophyta and Rhodophyta. In contrast, RLKs emerged more recently. Green algae harbour WAK-RLKs, Malectin-RLKs, and G-lectin-RLKs, and LysM-RLKs, L-lectin-RLKs, and Duf-26-RLKs are exclusive to Embryophytes (Fig. 2). Except for LRR-RLPs, all six families of RLP are basal to the RLK families.

In the AI science boom, beware: your results are only as good as your data

We are in the middle of a data-driven science boom. Huge, complex data sets, often with large numbers of individually measured and annotated ‘features’, are fodder for voracious artificial intelligence (AI) and machine-learning systems, with details of new applications being published almost daily.

But publication in itself is not synonymous with factuality. Just because a paper, method or data set is published does not mean that it is correct and free from mistakes. Without checking for accuracy and validity before using these resources, scientists will surely encounter errors. In fact, they already have.

In the past few months, members of our bioinformatics and systems-biology laboratory have reviewed state-of-the-art machine-learning methods for predicting the metabolic pathways that metabolites belong to, on the basis of the molecules’ chemical structures1. We wanted to find, implement and potentially improve the best methods for identifying how metabolic pathways are perturbed under different conditions: for instance, in diseased versus normal tissues.

Chemotherapy becomes more efficient when senescent cells are eliminated by immunotherapy, shows study

Cancer treatments, including chemotherapy, in addition to killing a large number of tumor cells, also result in the generation of senescent tumor cells (also called “zombie cells”). While senescent cells do not reproduce, they do, unfortunately, generate a favorable environment for the expansion of tumor cells that may have escaped the effects of the chemotherapy and eventually result in tumor regrowth.

An international team of researchers led by Dr. Manuel Serrano at IRB Barcelona has described in Nature Cancer how cells that have become senescent after chemotherapy activate the PD-L2 protein to protect themselves from the immune system while recruiting immune suppressor cells. The latter creates an inhibitory environment that impairs the ability of lymphocytes to kill cancer cells.

Based on these findings, scientists wondered what would be the effect of inactivating PD-L2. Interestingly, lacking PD-L2 are rapidly eliminated by the immune system. This intercepts the capacity of senescent cells to create an immunosuppressive environment and, as a result, lymphocytes retain their full capacity to kill those that may have escaped the effects of chemotherapy.

The Download: how babies can teach AI, and new mRNA vaccines

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 The world’s largest music label has yanked its artists’ music off TikTok Universal Music Group claims TikTok is unwilling to compensate musicians appropriately. (The Guardian) + Taylor Swift fans are kicking off. (Wired $) + Indie record labels don’t like the sound of Apple’s pay plans either. (FT $)

‘Heart-on-a-chip’ to test chemotherapies and other cancer drugs for heart toxicity

Chemotherapy can be toxic to heart cells. To help protect the hearts of cancer patients, Cedars-Sinai investigators have created a three-dimensional “heart-on-a-chip” to evaluate drug safety. In a study published in the journal Lab on a Chip, they show that the heart-on-a-chip, created using stem cells, accurately predicts the effects of drugs on human heart cells.

The investigators worked with induced pluripotent stem cells, which are that have been reprogrammed into stem cells and can be turned into any cell type in the body. They used the stem cells to create two types of heart cells, but instead of placing them all together in an unstructured cell culture dish, as is usually done in heart toxicity testing, the investigators introduced the cells into specialized chips.

The 3D chips feature two channels that are arranged to cross each other, keeping each cell type separate but allowing them to interact. The chips also allow for movement and the introduction of fluids.

New Medicine can Create a New Life for Diabetes Patients—Without Needles

There are approximately 425 million people worldwide with diabetes. Approximately 75 million of these inject themselves with insulin daily. Now, they may soon have a new alternative to syringes or insulin pumps. Scientists have found a new way to supply the body with smart insulin.

The new insulin can be eaten by taking a capsule or, even better, within a piece of chocolate.

Inside these are tiny nano-carriers in which the insulin is encapsulated. The particles are 1/10,000th the width of a human hair and so small that you cannot even see them under a normal microscope.

A nanotechnology‐based CRISPR/Cas9 delivery system for genome editing in cancer treatment

In the presence of protospacer adjacent motif (PAM), sgRNA accurately leads the Cas9 endonuclease to the target regions, where it causes DNA double strand breaks (DSBs), resulting in site‐specific genomic change. Endogenous DNA repair can take place following the creation of a DSB via two primary genome editing pathways: nonhomologous end joining (NHEJ) or homology‐directed repair (HDR).

By using the biological characteristics of Cas9 targeting specific DNA sequences under the guidance of sgRNA, scientists have further developed gene targeting activation and gene targeting inhibition tools based on dCas9, called CRISPRa and CRISPRi respectively.

In the paper, characteristics of three forms of CRISPR/Cas9 cargos are outlined. Three delivery forms of the CRISPR/Cas9 system are plasmids, mRNA/sgRNA, and ribonucleoprotein (RNP) complexes, each of which has its own advantages and disadvantages.

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