Biology subjects

Zhou, S.

Publications and source records attributed to Zhou, S..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

FKSFold: Improving AlphaFold3-Type Predictions of Molecular Glue-Induced Ternary Complexes with Feynman-Kac-Steered Diffusion

We introduce an AI model, FKSFold, that uses Feynman-Kac steered diffusion as an inference-time strategy to improve AlphaFold3-type predictions of molecular-glue induced ternary complexes. FKSFold augments reverse diffusion with a Feynman-Kac derived steering term and uses the interface predicted TM-score (ipTM) as the guiding potential, coupled with particle-based sampling and adaptive resampling to bias trajectories toward high-quality interfaces without retraining the base models. Implemented on Chai-1r and Boltz-2 (named FKSFold-Chai and FKSFold-Boltz) - two open-source AF3-type architectures - FKSFold was benchmarked on eight ternary systems. FKSFold-Chai recovered three challenging complexes with sub-3 [A] accuracy: VHL:MG:CDO1 (DockQ 0.922, iRMSD 0.629, fnat 0.963), FKBP12:MG:mTOR-FRB (DockQ 0.590, iRMSD 1.813, fnat 0.519), and FKBP12:MG:BRD9 (DockQ 0.841, iRMSD 0.801, fnat 0.913), while unmodified baselines failed. Other cases highlighted challenges - flexible loop rearrangements (e.g., CRBN:MG:VAV1-SH3c) and large conformational search spaces (e.g., NEK7, QDPR, HDAC1) - and, empirically, using few particles, short resampling intervals, and moderate-to-high lambda (steering strength) gave the best exploration-exploitation balance. Although the strategy is theoretically model-agnostic, on Boltz-2 ipTM head instability currently limits observed gains. The code for the two implementations, FKSFold-Chai and FKSFold-Boltz, is available at https://github.com/YDS-Pharmatech/FKSFold-Chai and https://github.com/YDS-Pharmatech/FKSFold-Boltz.

biophysics↗

bioRxiv2025

Control of leaflet movement pattern by a novel PP2C phosphatase DLM1 in Medicago truncatula

Sessile plants exhibit diverse movement behaviors that have long intrigued the scientists. The legume plants display a rhythmic leaflet movement pattern characterized by horizontal opening during the day and vertical closure at night. However, the underlying mechanisms remain largely enigmatic. Here, we isolated a mutant designated as dlm1 (downward leaflet movement1) from Medicago truncatula that displays leaflets downward opening during daytime while upward closure at night. Cellular analyses reveal that this aberrant phenotype correlates with abnormal volume changes of motor cells within the pulvinus. DLM1 exhibits high expression level in the motor organ pulvinus and encodes an unreported nuclear-localized PP2C phosphatase. Notably, phylogenetic analysis demonstrates that species exhibiting rhythmic leaflet movements consistently retain DLM1 homologs, suggesting the possibility of its functionally conserved role in regulating leaflets movement pattern. Structural characterization reveals that DLM1 possesses both phosphatase and kinase domains. Functional complementation assays demonstrate that the phosphatase domain is necessary and sufficient for maintaining the leaflet movement pattern. Collectively, our work uncovers a novel PP2C protein that governs the leaflet movement, providing mechanistic insights into this intriguing plant behavior.

plant biology↗

bioRxiv2025

Multiple evolutionary events in host plant adaptation in Lepidoptera

The evolution of insect host adaptation is a key component of insect-plant coevolution, a complex process often shaped by multiple evolutionary events. In this study, we identified two UDP-glycosyltransferase (UGT) genes, SfruUGT33T10 and SfruUGT33F32, in the fall armyworm Spodoptera frugiperda, which play critical roles in the tolerance of benzoxazinoids (BXs), secondary metabolites in maize. These two detoxification enzymes exhibited distinct glycosylation patterns for BXs and varying detoxification efficiencies, reflecting independent evolutionary trajectories. Phylogenetic analyses revealed that SfruUGT33T10 originated independently within Noctuidae, while SfruUGT33F32 resulted from tandem duplication within the UGT33F gene family and may have undergone neofunctionalization within the Spodoptera genus. Our findings provide evidence that the evolution of these two UGT paralogs contributed to the variation in the tolerance to maize BXs among different Lepidopteran species. This research underscores the significance of multiple independent evolutionary routes in host plant adaptation and offer new insights into the complex evolutionary processes underlying insect-plant interactions.

evolutionary biology↗

bioRxiv2025

Reshaping epistatic network modules enhances wheat yield potential

Increasing wheat yield is a key approach to ensuring global food security and an enduring focus in crop breeding. Here, we assembled a panel of 3,030 wheat lines to dissect the genetic mechanisms of yield improvement. We conducted large-scale field trials across five ecological environments over two consecutive years to evaluate yield performance and constructed a haplotype atlas using the Wheat 660K genotype array. 234 quantitative trait loci (QTLs) and 522 haplotype blocks (HBs) were identified for 14 traits through genome-wide association studies (GWAS), including 10 QTLs and 35 HBs associated with grain yield. Genomic analysis revealed that wheat yield improvement is primarily driven by changes in the epistatic network rather than the introduction of new haplotype segments. SNPs or HBs explain 53.3%-62.9% of the phenotypic variation in yield, whereas epistasis explains 70.4%, highlighting the role of epistasis in yield improvement. Moreover, yield improvement is significantly correlated with the accumulation of favorable epistatic modules. Pedigree-based analysis revealed that the modules remained relatively stable under the pressure of breeding selection, while new favorable modules were also created during hybrid breeding, highlighting that crop design breeding should be based on genetic modules. This study provides insights into genetic mechanism of wheat yield improvement and guidance for designing future wheat in the era of artificial intelligence.

genetics↗

bioRxiv2025

SB 11285, a Novel Canonical Purine-Pyrimidine Cyclic Dinucleotide, is a Systemically Bioavailable STING Agonist for Cancer Immunotherapy

SummarySB 11285, a novel cell-permeable, canonical 3,5, purine-pyrimidine cyclic dinucleotide has been developed as a potent systemically bioavailable STING agonist currently in clinical trials. The stimulator of Interferon genes (STING) pathway, crucial for cytosolic DNA sensing and innate immunity, presents a promising avenue for novel cancer immunotherapies. Discussed here is the discovery and development of SB11285, a potent activator of the STING pathway, belonging to the canonical class of 3,5 purine-pyrimidine (PuPy) cyclic dinucleotides (CDNs). SB11285 exhibits superior potency and cell permeability compared to non-canonical 2,3-CDNs and demonstrates robust antitumor activity in in vivo syngeneic mouse tumor models, resulting in complete tumor regression, and durable immunological memory. Combination with checkpoint inhibitors and cytotoxic agents further enhances its efficacy. The anti-tumor effects of SB 11285 rely on the induction of CD8+ T cells, activated macrophages, and NK cells in the tumor microenvironment (TME), for efficient tumor killing and fostering profound and durable anti-tumor response. Our findings underscore the potential of functionalized canonical 3,5-Pu-Py CDNs, exemplified by SB11285, as safe and potent STING agonists for multiple routes of administration in cancer therapy. Currently, SB11285 administered intravenously (IV), is undergoing evaluation as the first systemically administered CDN analog in human clinical trials across various tumor types.

immunology↗

bioRxiv2025

CDK12 condensation in nuclear speckles confers sensitivity to cyclin K molecular glue degraders

Transcriptional machinery often operates in the configuration of biomolecular condensates, presenting emerging opportunities to develop therapies targeting transcriptionally addicted malignancies. In this study, we discovered that cyclin-dependent kinase 12 (CDK12), a key regulator of transcription elongation, formed dynamic liquid-like droplets within nuclear speckles, a process enhanced by high CDK12 expression and CDK12 inhibitor treatment. Recognizing this unique property, we rationally designed ZSQ253, a modular cyclin K molecular glue degrader that coupled binding moieties for both CDK12 and DDB1. By promoting phase separation-driven assembly and subsequent proteasomal degradation of the CDK12-cyclin K complex, ZSQ253 interfered with oncogenic transcription and demonstrated potent antitumor capability. Further structure-guided optimization yielded HQY1428, a derivative with a multi-site gluing effect and improved drug activity. Given the frequent genomic co-amplification of CDK12 and ERBB2 across diverse human cancers, we showed that combining HQY1428 with HER2 inhibitors provided synergistic therapeutic benefits. Collectively, our findings establish CDK12 condensation within nuclear speckles as an exploitable vulnerability, and introduce a novel mechanism of action underlying cyclin K molecular glue degraders.

cancer biology↗

bioRxiv2025

The neurocomputational mechanisms of hierarchical linguistic predictions during narrative comprehension

Language comprehension requires a listener to predict the upcoming inputs of linguistic units with multiple timescales based on previous contexts, but how the prediction process is hierarchically represented and implemented in the human brain remains unclear. Combining the natural language processing (NLP) approach and functional Magnetic Resonance Imaging (fMRI) in a narrative comprehension task, we first applied the group-based general linear model (gGLM) to identify the neural underpinnings associated with the language prediction on word and sentence. Our results revealed a cortical architecture supporting the prediction, extending from the superior temporal cortices to the regions in the default mode network. Then, we investigated how these adjacent levels interact with each other by testing two rival hypotheses: the continuous updating hypothesis posits that the higher level of the representational hierarchy is continuously updated as inputs unfold over time, while the sparse updating hypothesis states that the higher level is only updated at the end of their preferred timescales of linguistic units. By conducting computational modeling and autocorrelation analysis, we found the sparse model outperformed the continuous model and the updating might occur at the sentence boundaries. Together, our results extend the linguistic prediction from the small timescales such as words to large timescales such as sentences, providing novel insights into the neurocomputational mechanisms of information updating within the linguistic prediction hierarchy.

neuroscience↗

bioRxiv2025

METTL1/WDR4-mediated m7G Hypermethylation of SCLT1 mRNA Promotes Gefitinib Resistance in Non-small Cell Lung Cancer

Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) have produced durable complete responses, but the eventual development of acquired resistance presents a huge challenge in the treatment of non-small cell lung cancer (NSCLC). N7-methylguanosine (m7G), a prevalent post-transcriptional modification within RNA, play regulatory roles in RNA stability, expression dynamics, and functional diversity. Despite these insights, the contribution of m7G methylation to EGFR-TKIs resistance remains poorly characterized. Here, we identified substantial upregulation of mRNA internal m7G modifications and their associated methyltransferase complex composed of methyltransferase-like 1 (METTL1) /WD repeat domain 4 (WDR4) were significantly elevated in NSCLC specimens, correlating with therapeutic resistance. Functional assays confirmed that METTL1/WDR4 enhances gefitinib resistance in both cellular and animal models via the internal RNA m7G methyltransferase activity in NSCLC. Mechanistically, m7G MeRIP-seq coupled with RNA-seq identified sodium channel and clathrin linker 1 (SCLT1) as the m7G target of METTL1/WDR4. METTL1/WDR4 knockdown may result in a decrease in both the demethylation level and mRNA stability of the SCLT1 transcript, while overexpression of wild-type METTL1, but not its catalytically inactive mutant, rescues mRNA stability. METTL1/WDR4-mediated m7G modification of SCLT1 regulates gefitinib resistance by activating the NF-{kappa}B signaling. These results establish aberrant mRNA internal m7G modification as a novel resistance mechanism and propose therapeutic targeting of the METTL1/WDR4-SCLT1-NF-{kappa}B axis cascade to overcome EGFR-TKIs resistance.

molecular biology↗

bioRxiv2025

Manganese suppresses tumor growth through hyper-activating IRE1α

IRE1 and its downstream XBP1 signal is the most conserved unfolded protein response pathway that cells utilize to combat endoplasmic reticulum stress, also known to be utilized by tumor cells to adapt to harsh environment, leading to tumor progression. Several inhibitors against IRE1 have been developed, some of which show promising effect in clinical trial for cancer therapy, but none of them have been used in practice. Considering that hyper-activation of IRE1 induces cell death, we hypothesize that activation of IRE1 could be an alternative way for tumor suppression. Here, we identified divalent manganese ion as a potent activator to IRE1, which interacts with the cytosolic part of IRE1 directly, augmenting the downstream pro-apoptotic pathway but not the pro-survival outcome. Mn2+ limits tumor growth in xenograft model in an IRE1-dependent way. Our finding suggests pharmacological activation of IRE1 as an underestimated but promising way in cancer therapy. HighlightsO_LIMn2+ binds to cytosolic segment of IRE1 and promotes its oligomerization C_LIO_LIMn2+ hyper-activates IRE1 and induces downstream terminal UPR under ER stress C_LIO_LIMn2+ does not elevate XBP1s expression C_LIO_LIMn2+ as an IRE1 activator impairs tumor growth in xenograft model C_LI

cancer biology↗

bioRxiv2025

LivecellX: A Deep-learning-based, Single-Cell Object-Oriented Framework for Quantitative Analysis in Live-Cell Imaging

Live-cell imaging uniquely captures single-cell dynamics in space and time, but robust analysis is limited by segmentation and tracking errors that accumulate across frames. We present LivecellX, a deep-learning-based pipeline that integrates instance-level segmentation error correction with trajectory refinement, leveraging temporal context to recover accurate cell tracks. LivecellX also introduces a benchmark dataset with detailed annotations of common error classes, providing a resource for method development and evaluation. Beyond error correction, the framework incorporates modules for classifying biological processes, reconstructing cell lineages, and analyzing dynamic behaviors. Users can interact with the system programmatically or through a Napari-based graphical interface, enabling flexible integration into diverse workflows. By coupling error-aware correction with comprehensive lineage and dynamics analysis, LivecellX establishes an open, extensible platform that advances the accuracy and scalability of live-cell imaging studies.

biophysics↗

bioRxiv2025

Ancient human extinction risk: Implications from high-precision computation and fossil evidence

Reconstructing ancient population size history is essential for understanding the evolutionary origin of Homo sapiens. Using the fast infinitesimal time coalescent process (FitCoal), which precisely computes the expected site frequency spectrum (SFS), we revisited the debated population bottleneck that occurred approximately 930 thousand years ago. By benchmarking FitCoal against mushi and ten billion coalescent simulations, we demonstrate that FitCoal achieves both superior speed and accuracy in expected SFS estimation. Analyses of simulated datasets confirmed that FitCoal reliably recovered the bottleneck, whereas mushi failed under identical conditions. Independent fossil and paleoclimate evidence further corroborates the timing and evolutionary impact of this bottleneck, linking it to hominin dispersals, speciation events, and a subsequent increase in brain size. These findings refine the demographic history of Homo during the Pleistocene and highlight the importance of high-precision SFS computation for revealing critical evolutionary transitions that shaped modern human ancestry.

evolutionary biology↗

bioRxiv2025

A Sensitive Soma-localized Red Fluorescent Calcium Indicator for Multi-Modality Imaging of Neuronal Populations In Vivo

Recent advancements in genetically encoded calcium indicators, particularly those based on green fluorescent proteins, have optimized their performance for monitoring neuronal activities in a variety of model organisms. However, progress in developing red-shifted GECIs, despite their advantages over green indicators, has been slower, resulting in fewer options for end-users. In this study, we explored topological inversion and soma-targeting strategies, which are complementary to conventional mutagenesis, to re-engineer a red genetically encoded calcium indicator, FRCaMP, for enhanced in vivo performance. The resulting sensors, FRCaMPi and soma-targeted FRCaMPi (SomaFRCaMPi), exhibit up to 2-fold higher dynamic range and peak {Delta}F/F0 per single AP compared to widely used jRGECO1a in neurons in culture and in vivo. Compared to jRGECO1a and FRCaMPi, SomaFRCaMPi reduces erroneous correlation of neuronal activity in the brains of mice and zebrafish by two- to four-fold due to diminished neuropil contamination without compromising the signal-to-noise ratio. Under wide-field imaging in primary somatosensory and visual cortex in mice with high labeling density (80-90%), SomaFRCaMPi exhibits up to 40% higher SNR and decreased artifactual correlation across neurons. Altogether, SomaFRCaMPi improves the accuracy and scale of neuronal activity imaging at single-neuron resolution in densely labeled brain tissues due to a 2-3-fold enhanced automated neuronal segmentation, 50% higher fraction of responsive cells, up to 2-fold higher SNR compared to jRGECO1a. Our findings highlight the potential of SomaFRCaMPi, comparable to the most sensitive soma-targeted GCaMP, for precise spatial recording of neuronal populations using popular imaging modalities in model organisms such as zebrafish and mice.

neuroscience↗

bioRxiv2025

HIV-1 Rebound Virus Consists of a Small Number of Lineages That Entered the Reservoir Close to ART Initiation

HIV-1 persists as a latent reservoir during suppressive antiretroviral therapy (ART). Viral rebound occurs upon ART interruption, posing a challenge to cure efforts. Characterizing viral populations fuelling rebound is imperative to curing HIV-1. We used longitudinal samples collected pretherapy from women in the CAPRISA 002 cohort to create an evolutionary time- line to determine the pretherapy timepoint when the rebound virus originally entered the long- lived reservoir. Participants (N=10) were untreated for an average of 5 years then on ART for an average of 2 years before viral rebound (defined as >1000 RNA copies/ml). env sequences were used to characterize the longitudinal pre-ART evolving viral RNA population, the proviral DNA reservoir during ART, and viral RNA in the plasma during rebound. For each participant, between 1 and 3 major viral lineages were identified in the plasma during rebound. A total of 20 rebound virus lineages were examined for the 10 participants, and 19 were found to have entered the reservoir around the time of therapy initiation. The one lineage estimated to enter the reservoir more than a year before therapy was observed in a participant who was untreated for more than 8 years, yet retained moderate CD4 T cell counts. Analysis of the viral DNA reservoir, from which the rebound viruses emanated, revealed that while 95% of rebounding lineages dated to the year before ART initiation, only 61% of unique proviruses dated to that time period. Strikingly, for three participants with DNA reservoirs dominated by viruses from earlier in untreated infection, only 33% of unique proviruses dated to the year before ART initiation, yet 83% of rebounding lineages dated to that time. Our results show that rebound virus almost exclusively comes from the portion of the latent reservoir that formed around the time of therapy initiation, even when the reservoir is composed of diverse sequences from across the pre-ART time period. Author SummaryHIV-1 is maintained in a long-lived reservoir during suppressive therapy. Virus rebounds if therapy is discontinued. We found that in most cases rebound virus comes from a pool of viral sequences that entered the long-lived reservoir around the time of therapy initiation. While the viral DNA reservoir is on average also skewed toward sequences replicating around the time of therapy initiation, the rebound virus almost exclusively comes from this portion of the latent reservoir, even when the reservoir contained proviruses from much earlier in untreated infection. Thus, we hypothesize that there are features of the viruses forming the latent reservoir around the time of therapy initiation, or features of the host at that time, that select these viruses as initiators of rebound during therapy discontinuation.

microbiology↗

bioRxiv2025

Lower spatial turnover of rare fungal taxa dominantly shaped by stochastic processes in grassland soils

The spatial pattern and community assembly of soil microbial taxa have notable meanings for biodiversity shaping and maintaining mechanisms. Rare fungal taxa may exhibit distinct patterns and assembly mechanisms compared to abundant taxa, but such information is limited, especially at large scales. Here, we investigated distance-decay patterns and underlying assembly mechanisms for abundant and rare fungal taxa in 129 soil samples collected across 4,000 km in Chinese Northern grasslands, based on high-throughput sequencing data. A total of 208 abundant OTUs (relative abundance > 0.1%, 2.73% of entire OTUs) and 5,779 rare OTUs (relative abundance < 0.01%, 75.85% of entire OTUs) were identified. Both abundant and rare fungal taxa showed significant distance-decay relationships (P < 0.001), but the turnover rate for rare taxa (0.0024 per 100 km) was nearly half that of abundant taxa (0.0054 per 100 km) based on the binary Bray-Curtis distance. The lower turnover of rare fungal taxa was likely due to their community assembly mechanism dominated by stochastic processes, which were less influenced by environmental gradients. In contrast, abundant taxa assembly was dominated by deterministic factors like soil variables and plant traits, which varied significantly along the geographic distance. Consistently, rare fungal taxa were also less sensitive to environmental changes, with a lower turnover rate by environmental distance (0.0027 vs. 0.0099) than abundant taxa. In summary, our findings revealed that rare fungal taxa, shaped mainly by stochastic processes, had lower spatial turnover compared to abundant taxa, dominated by deterministic processes, enhancing our understanding of rare microbial biogeography.

ecology↗

bioRxiv2025

PARAS: high-accuracy machine-learning of substrate specificities in nonribosomal peptide synthetases

Nonribosomal peptides are diverse natural products with important applications in medicine and agriculture. Bacterial and fungal genomes contain thousands of nonribosomal peptide biosynthetic gene clusters (BGCs) of unknown function, providing a promising resource for peptide discovery. Core structural features of such peptides can be inferred by predicting the substrate(s) of adenylation (A) domains in nonribosomal peptide synthetases (NRPSs). However, existing approaches to A domain prediction rely on limited datasets and often struggle with domains selecting large substrates or from less-studied taxa. Here, we systematically curate and computationally analyse 3,653 A domains and present two high-accuracy specificity predictors, PARAS and PARASECT. A type of A domain with unusually high L-tryptophan specificity was identified through the application of PARAS, and intact protein mass spectrometry to the corresponding NRPS showed it to direct the production of tryptopeptin-related metabolites in Streptomyces species. Together, these technologies will accelerate the characterisation of novel NRPSs and their metabolic products. PARAS and PARASECT are available at https://paras.bioinformatics.nl. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/631717v2_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@8e48aaorg.highwire.dtl.DTLVardef@144c78dorg.highwire.dtl.DTLVardef@890c11org.highwire.dtl.DTLVardef@1776de9_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2024

Genetically Encoded Red Fluorescent Indicators for Imaging Intracellular and Extracellular Potassium Ions

Potassium ion (K+) dynamics are vital for various biological processes. However, the limited availability of detection tools for tracking intracellular and extracellular K+ has impeded a comprehensive understanding of the physiological roles of K+ in intact biological systems. In this study, we developed two novel red genetically encoded potassium indicators (RGEPOs), RGEPO1 and RGEPO2, through a combination of directed evolution in E. coli and subsequent optimization in mammalian cells. RGEPO1, targeted to the extracellular membrane, and RGEPO2, localized in the cytoplasm, exhibited positive K+-specific fluorescence response with affinities of 3.55 mM and 14.81 mM in HEK293FT cells, respectively. We employed RGEPOs for real-time monitoring of subsecond K+ dynamics in cultured neurons, astrocytes, acute brain slices, and the awake mouse in both intracellular and extracellular environments. Using RGEPOs, we were able, for the first time, to visualize intracellular and extracellular potassium transients during seizures in the brains of awake mice. Furthermore, molecular dynamics simulations provided new insights into the potassium-binding mechanisms of RGEPO1 and RGEPO2, revealing distinct K+-binding pockets and structural features. Thus, RGEPOs represent a significant advancement in potassium imaging, providing enhanced tools for real-time visualization of K+ dynamics in various cell types and cellular environments.

biochemistry↗

bioRxiv2024

PD-L1 expression is mediated by microRNA processing, Wnt/β-catenin signaling, and chemotherapy in Wilms tumor

Inhibition of immune checkpoint proteins is effective in adult cancers but has shown limited efficacy in pediatric cancers. While factors regulating expression of immune checkpoint proteins such as PD-L1 are well-documented in adult cancers, their regulation is poorly understood in pediatric cancers. Here, we show that PD-L1 is upregulated in distinct subsets of Wilms tumor, the most common pediatric kidney cancer. Specifically, chemotherapy-exposed Wilms tumor specimens exhibited higher levels of PD-L1 expression, and common chemotherapeutics upregulated PD-L1 in childhood cancer cell lines in vitro. Furthermore, mutations in CTNNB1 and DROSHA, the two most commonly mutated genes in Wilms tumor, correlated with higher PD-L1. Activation of Wnt/{beta}-catenin signaling and knockdown of DROSHA or DICER1 both increase PD-L1 in vitro. Lastly, in adult cancers, DICER1 alterations are associated with immune gene expression signatures and improved survival in response to immune checkpoint inhibitors. Together, our results identify clinical and biological properties regulating PD-L1 in Wilms tumor that may inform precision therapy approaches in pediatric immuno-oncology.

cancer biology↗

bioRxiv2024

Temperature, but not plant cultivar, influence the efficacy of insecticidal dsRNA in Colorado potato beetle

Environmental RNAi (eRNAi) is a recent innovation in insect pest control, and comprehensive risk assessment is needed to ensure the environmental safety and longevity of this technology. As eRNAi relies on the insects cellular machinery for its mode of action, environmentally mediated plasticity in the activity of cellular processes required for RNAi could influence efficacy and the development of resistance. Here, we investigated the extent to which plant cultivar and temperature influence the efficacy of insecticidal double-stranded RNA (dsRNA) targeting actin in larvae of the Colorado potato beetle (CPB; Leptinotarsa decemlineata). Potato cultivar did not significantly affect survival or gene silencing in dsRNA-treated larvae, indicating that efficacy is consistent across potato varieties, at least under laboratory conditions. However, the amount of leaf tissue consumed by larvae varied across cultivars, with consumption being inversely proportional to protein content. Thus, the ingested dose of dsRNA may vary across crop varieties. Temperature did influence RNAi efficacy, with both gene silencing and mortality being reduced when dsRNA treatment occurred at lower temperatures. After three days of feeding with dsRNA, gene silencing occurred at all temperatures, but knockdown efficiency was 62% at 30{degrees}C and 35% at 18{degrees}C. Beetles consumed significantly less leaf tissue (and thus dsRNA) at 18{degrees}C, but the observed temperature-dependent effects could not be fully explained by the quantity of dsRNA ingested. Further, efficacy at different temperatures was not related to transcript levels of core RNAi genes, indicating that other mechanisms are responsible for the observed effects. Overall, these results indicate that environmental conditions can influence the efficacy of insecticidal eRNAi and may affect the rate at which insects develop resistance to these technologies.

molecular biology↗