Artificial intelligence assistance for fetal development: evaluation of an automated software for biometry measurements in the mid-trimester.

BACKGROUND: This study presents CUPID, an advanced automated measurement software based on Artificial Intelligence (AI), designed to evaluate nine fetal biometric parameters in the mid-trimester. Our primary objective was to assess and compare the CUPID performance of experienced senior and junior radiologists. MATERIALS AND METHODS: This prospective cross-sectional study was conducted at Shenzhen University General Hospital between September 2022 and June 2023, and focused on mid-trimester fetuses. All ultrasound images of the six standard planes, that enabled the evaluation of nine biometric measurements, were included to compare the performance of CUPID through subjective and objective assessments. RESULTS: There were 642 fetuses with a mean (±SD) age of 22 ± 2.82 weeks at enrollment. In the subjective quality assessment, out of 642 images representing nine biometric measurements, 617-635 images (90.65-96.11%) of CUPID caliper placements were determined to be accurately placed and did not require any adjustments. Whereas, for the junior category, 447-691 images (69.63-92.06%) were determined to be accurately placed and did not require any adjustments. In the objective measurement indicators, across all nine biometric parameters and estimated fetal weight (EFW), the intra-class correlation coefficients (ICC) (0.843-0.990) and Pearson correlation coefficients (PCC) (0.765-0.978) between the senior radiologist and CUPID reflected good reliability compared with the ICC (0.306-0.937) and PCC (0.566-0.947) between the senior and junior radiologists. Additionally, the mean absolute error (MAE), percentage error (PE), and average error in days of gestation were lower between the senior and CUPID compared to the difference between the senior and junior radiologists. The specific differences are as follows: MAE (0.36-2.53 mm, 14.67 g) compared to (0.64- 8.13 mm, 38.05 g), PE (0.94-9.38%) compared to (1.58-16.04%), and average error in days (3.99-7.92 days) compared to (4.35-11.06 days). In the time-consuming task, CUPID only takes 0.05-0.07 s to measure nine biometric parameters, while senior and junior radiologists require 4.79-11.68 s and 4.95-13.44 s, respectively. CONCLUSIONS: CUPID has proven to be highly accurate and efficient software for automatically measuring fetal biometry, gestational age, and fetal weight, providing a precise and fast tool for assessing fetal growth and development.

Locating Multiple Standard Planes in First-Trimester Ultrasound Videos via the Detection and Scoring of Key Anatomical Structures.

OBJECTIVE: This study was aimed at developing a first-trimester standard plane detection (FTSPD) system that can automatically locate nine standard planes in ultrasound videos and investigating its utility in clinical practice. METHODS: The FTSPD system, based on the YOLOv3 network, was developed to detect structures and evaluate the quality of plane images by using a pre-defined scoring system. A total of 220 videos from two different ultrasound scanners were collected to compare detection performance between our FTSPD system and sonographers with different levels of experience. The quality of the detected standard planes was quantitatively rated by an expert according to a scoring protocol. Kolmogorov-Smirnov analysis was used to compare the distributions of scores across all nine standard planes. RESULTS: The expert-rated scores indicated that the quality of the standard planes detected by the FTSPD system was on par with that of the planes detected by senior sonographers. There were no significant differences in the distributions of the scores across all nine standard planes. The FTSPD system performed significantly better than junior sonographers in five standard plane types. CONCLUSION: The results of this study suggest that our FTSPD system has significant potential for detecting standard planes in first-trimester ultrasound screening, which may help to improve the accuracy of fetal ultrasound screening and facilitate early diagnosis of abnormalities. The quality of the standard planes selected by junior sonographers can be significantly improved with the assistance of our FTSPD system.

RecON: Online learning for sensorless freehand 3D ultrasound reconstruction.

Sensorless freehand 3D ultrasound (US) reconstruction based on deep networks shows promising advantages, such as large field of view, relatively high resolution, low cost, and ease of use. However, existing methods mainly consider vanilla scan strategies with limited inter-frame variations. These methods thus are degraded on complex but routine scan sequences in clinics. In this context, we propose a novel online learning framework for freehand 3D US reconstruction under complex scan strategies with diverse scanning velocities and poses. First, we devise a motion-weighted training loss in training phase to regularize the scan variation frame-by-frame and better mitigate the negative effects of uneven inter-frame velocity. Second, we effectively drive online learning with local-to-global pseudo supervisions. It mines both the frame-level contextual consistency and the path-level similarity constraint to improve the inter-frame transformation estimation. We explore a global adversarial shape before transferring the latent anatomical prior as supervision. Third, we build a feasible differentiable reconstruction approximation to enable the end-to-end optimization of our online learning. Experimental results illustrate that our freehand 3D US reconstruction framework outperformed current methods on two large, simulated datasets and one real dataset. In addition, we applied the proposed framework to clinical scan videos to further validate its effectiveness and generalizability.

Test-time bi-directional adaptation between image and model for robust segmentation.

BACKGROUND AND OBJECTIVE: Deep learning models often suffer from performance degradations when deployed in real clinical environments due to appearance shifts between training and testing images. Most extant methods use training-time adaptation, which almost require target domain samples in the training phase. However, these solutions are limited by the training process and cannot guarantee the accurate prediction of test samples with unforeseen appearance shifts. Further, it is impractical to collect target samples in advance. In this paper, we provide a general method of making existing segmentation models robust to samples with unknown appearance shifts when deployed in daily clinical practice. METHODS: Our proposed test-time bi-directional adaptation framework combines two complementary strategies. First, our image-to-model (I2M) adaptation strategy adapts appearance-agnostic test images to the learned segmentation model using a novel plug-and-play statistical alignment style transfer module during testing. Second, our model-to-image (M2I) adaptation strategy adapts the learned segmentation model to test images with unknown appearance shifts. This strategy applies an augmented self-supervised learning module to fine-tune the learned model with proxy labels that it generates. This innovative procedure can be adaptively constrained using our novel proxy consistency criterion. This complementary I2M and M2I framework demonstrably achieves robust segmentation against unknown appearance shifts using existing deep-learning models. RESULTS: Extensive experiments on 10 datasets containing fetal ultrasound, chest X-ray, and retinal fundus images demonstrate that our proposed method achieves promising robustness and efficiency in segmenting images with unknown appearance shifts. CONCLUSIONS: To address the appearance shift problem in clinically acquired medical images, we provide robust segmentation by using two complementary strategies. Our solution is general and amenable for deployment in clinical settings.

Site-directed integration of exogenous DNA into the soybean genome by LbCas12a fused to a plant viral HUH endonuclease.

High efficiency site-directed chromosomal integration of exogenous DNA in plants remains a challenge despite recent advances in genome editing technologies. One approach to mitigate this problem is to increase the effective concentration of the donor DNA at the target site of interest. HUH endonucleases (ENs) coordinate rolling circle replication. In vitro, they can form stable covalent bonds with DNA that carries their recognition motifs. When fused to a CRISPR-associated endonuclease, HUH ENs may improve integration rates by increasing the local donor concentration through tethering of the donor to the CRISPR nuclease. We tested this hypothesis by using chimeric proteins between LbCas12a as a CRISPR-associated endonuclease and the HUH EN from Faba Bean Necrotic Yellow Virus in soybean (Glycine max). Two fusion protein configurations were tested to integrate a 70-nt oligonucleotide donor into a commercially important target site using protoplasts and in planta transformation. Site-directed integration rates of the donor DNA, when tethered to the fusion protein, reached about 26% in plants and were up to four-fold higher than in untethered controls. Integrations via canonical homology-directed repair or non-homologous end joining were promoted by tethering in a similar fashion. This study is the first demonstration of HUH EN-associated tethering to improve site-directed DNA integration in plants.

Network Pharmacology Deciphers the Action of Bioactive Polypeptide in Attenuating Inflammatory Osteolysis via the Suppression of Oxidative Stress and Restoration of Bone Remodeling Balance.

Oxidative stress involves enormously in the development of chronic inflammatory bone disease, wherein the overproduction of reactive oxygen species (ROS) negatively impacts the bone remodeling via promoting osteoclastogenesis and inhibiting osteogenesis. Lacking effective therapies highlights the importance of finding novel treatments. Our previous study screened a novel bioactive peptide D7 and demonstrated it could enhance the cell behaviors and protect bone marrow mesenchymal stem cells (BMSCs). Since BMSCs are progenitor cells of osteoblast (OB), we therefore ask whether D7 could also protect against the progress of inflammatory osteolysis. To validate our hypothesis and elucidate the underlying mechanisms, we first performed network pharmacology-based analysis according to the molecule structure of D7, and then followed by pharmacological evaluation on D7 by in vitro lipopolysaccharide(LPS)-induced models. The result from network pharmacology identified 20 candidate targets of D7 for inflammatory osteolysis intervention. The further analysis of Gene Ontology (GO)/KEGG pathway enrichment suggested the therapeutic effect of D7 may primarily affect osteoclast (OC) differentiation and function during the inflammatory osteolysis. Through validating the real effects of D7 on OC and OB as postulated, results demonstrated suppressive effects of D7 on LPS-stimulated OC differentiation and resorption, via the inhibition on OC marker genes. Contrarily, by improving the expression of OB marker genes, D7 displayed promotive effects on OB differentiation and alleviated LPS-induced osteogenic damage. Further mechanism study revealed that D7 could reduce LPS-induced ROS formation and strengthen antioxidants expressions in both OC and OB precursors, ameliorating LPS-triggered redox imbalance in bone remodeling. Taken together, our findings unveiled therapeutic effects of D7 against LPS-induced inflammatory osteolysis through the suppression of oxidative stress and the restoration of the bone remodeling process, providing a new therapeutic candidate for chronic inflammatory bone diseases.

Searching collaborative agents for multi-plane localization in 3D ultrasound.

3D ultrasound (US) has become prevalent due to its rich spatial and diagnostic information not contained in 2D US. Moreover, 3D US can contain multiple standard planes (SPs) in one shot. Thus, automatically localizing SPs in 3D US has the potential to improve user-independence and scanning-efficiency. However, manual SP localization in 3D US is challenging because of the low image quality, huge search space and large anatomical variability. In this work, we propose a novel multi-agent reinforcement learning (MARL) framework to simultaneously localize multiple SPs in 3D US. Our contribution is four-fold. First, our proposed method is general and it can accurately localize multiple SPs in different challenging US datasets. Second, we equip the MARL system with a recurrent neural network (RNN) based collaborative module, which can strengthen the communication among agents and learn the spatial relationship among planes effectively. Third, we explore to adopt the neural architecture search (NAS) to automatically design the network architecture of both the agents and the collaborative module. Last, we believe we are the first to realize automatic SP localization in pelvic US volumes, and note that our approach can handle both normal and abnormal uterus cases. Extensively validated on two challenging datasets of the uterus and fetal brain, our proposed method achieves the average localization accuracy of 7.03∘/1.59mm and 9.75∘/1.19mm. Experimental results show that our light-weight MARL model has higher accuracy than state-of-the-art methods.

Agent With Warm Start and Adaptive Dynamic Termination for Plane Localization in 3D Ultrasound.

Accurate standard plane (SP) localization is the fundamental step for prenatal ultrasound (US) diagnosis. Typically, dozens of US SPs are collected to determine the clinical diagnosis. 2D US has to perform scanning for each SP, which is time-consuming and operator-dependent. While 3D US containing multiple SPs in one shot has the inherent advantages of less user-dependency and more efficiency. Automatically locating SP in 3D US is very challenging due to the huge search space and large fetal posture variations. Our previous study proposed a deep reinforcement learning (RL) framework with an alignment module and active termination to localize SPs in 3D US automatically. However, termination of agent search in RL is important and affects the practical deployment. In this study, we enhance our previous RL framework with a newly designed adaptive dynamic termination to enable an early stop for the agent searching, saving at most 67% inference time, thus boosting the accuracy and efficiency of the RL framework at the same time. Besides, we validate the effectiveness and generalizability of our algorithm extensively on our in-house multi-organ datasets containing 433 fetal brain volumes, 519 fetal abdomen volumes, and 683 uterus volumes. Our approach achieves localization error of 2.52mm/10.26° , 2.48mm/10.39° , 2.02mm/10.48° , 2.00mm/14.57° , 2.61mm/9.71° , 3.09mm/9.58° , 1.49mm/7.54° for the transcerebellar, transventricular, transthalamic planes in fetal brain, abdominal plane in fetal abdomen, and mid-sagittal, transverse and coronal planes in uterus, respectively. Experimental results show that our method is general and has the potential to improve the efficiency and standardization of US scanning.

A Preliminary Comparative Study of Young's Modulus Versus Shear Modulus in the Diagnosis of Breast Cancer.

PURPOSE: The purpose of this study was to compare the diagnostic value of Young's modulus (E) and shear modulus (G) in the differential diagnosis of benign and malignant breast masses using sound touch elastography (STE) and to explore the relationship between G and E in breast lesions. METHODS: A total of 96 consecutive women with 110 pathologically confirmed breast masses were included. All masses were detected by conventional and STE ultrasound. Emean, Emax, Emin, ESD, Gmean, Gmax, Gmin, and GSD were determined and evaluated for evidence of significant differences between benign and malignant breast masses. Receiver operator characteristics were used to compare the diagnostic efficacy of E and G and to determine the G cutoff value that would aid in the differential diagnosis of breast cancer. RESULTS: Emean, Emax, ESD, Gmean, Gmax, and GSD in cases of malignant breast masses were significantly higher than those in cases of benign masses (P < 0.05). There was no significant difference between Emin and Gmin (P = 0.565). In applying the Emean, Emax, ESD, Gmean, Gmax, and GSD to the receiver operator characteristics: (1) the area under the curve (AUC) of Gmean and Gmax is greater than the AUC of Emean and Emax, and the AUC of ESD is equal to the AUC of GSD. (2) The sensitivity and specificity were highest when the Gmean was 10.14 kPa. They were 84.1% and 80.3% respectively. (3) The sensitivity and specificity were highest when the Gmax was 52.20 kPa. They were 88.6% and 87.9% respectively. CONCLUSIONS: These preliminary results of STE evaluation of breast masses suggest that the diagnostic value of G is greater than E. Furthermore, STE is a valuable tool in the differential diagnosis of breast lesions.

Exosomes derived from platelet-rich plasma present a novel potential in alleviating knee osteoarthritis by promoting proliferation and inhibiting apoptosis of chondrocyte via Wnt/ß-catenin signaling pathway.

BACKGROUND: Platelet-rich plasma (PRP) provides a nonsurgical approach for treating osteoarthritis (OA). Exosomes that play vital roles in intercellular communication have been studied extensively. Here, we investigated the therapeutic potential and molecular mechanism of exosomes derived from PRP (PRP-Exos) in alleviating OA. METHODS: Exosomes derived from PRP(PRP-Exos) were isolated and purified using the exoEasy Maxi Kit and then identified and analyzed. Primary rabbit chondrocytes were isolated and treated with interleukin 1 beta (IL-1ß) to establish the OA model in vitro. Proliferation, migration, and apoptosis assays were measured and compared between PRP-Exos and activated PRP (PRP-As) to evaluate the therapeutic effects on OA. The mechanism involving the Wnt/ß-catenin signaling pathway was investigated by Western blot analysis. In vivo, we established animal knee OA model by surgery to compare the therapeutic effect of PRP-Exos and PRP-As. RESULTS: We successfully isolated and purified exosomes from PRP using the exoEasy Maxi Kit. We also isolated and identified chondrocytes from the New Zealand white rabbit and established the IL-1ß-induced OA model; meanwhile, PRP-Exos and PRP-As both inhibited the release of tumor necrosis factor-α(TNF-α) and there was no statistically significant difference between the two. In proliferation, migration, scratch assay, the promoting effect of PRP-Exos was significantly more better than PRP-As. Furthermore, PRP-Exos could significantly decreased apoptotic rate of OA chondrocyte compared with PRP-As. In Western blot analysis, the expression of ß-catenin, and RUNX2, Wnt5a were increased in IL-1ß-treated chondrocytes, but PRP-Exos and PRP-As could both reverse these changes, and the reversal effect of the former was better than the latter. In vivo, we found that both PRP-Exos and PRP-As displayed the progression of OA, and the effect of PRP-Exos was obviously better than PRP-As by chondrocyte count and Osteoarthritis Research Society International (OARSI) scoring system. CONCLUSION: The therapeutic effects of PRP-Exos on OA were similar or better compared with those of PRP-As in vitro or in vivo. PRP-Exos acting as carriers containing growth factors derived from PRP present a novel therapy for OA by activating the Wnt/ß-catenin signaling pathway.

Endogenous tassel-specific small RNAs-mediated RNA interference enables a novel glyphosate-inducible male sterility system for commercial production of hybrid seed in Zea mays L.

Hybrid crops produce higher yields than their inbred parents due to heterosis. For high purity of hybrid seeds, it is critical to eliminate self-pollination. Manual or mechanical removal of male parts (such as detasseling in maize) is labor-intensive, fuel and time-consuming, and can cause physical damage to female plants, resulting in significant seed yield reductions. Many male-sterility systems either require a maintainer for male-sterile line propagation or are often affected by environmental factors. Roundup® Hybridization System (RHS) utilizes glyphosate to induce male sterility, which effectively eliminates the need for maintainer lines and removal of male parts for commercial hybrid seed production. The first-generation RHS (RHS1) is based on low expression of a glyphosate-insensitive 5-enolpyruvylshikimate-3-phosphate synthase (CP4 EPSPS) in pollen. This report presents the second-generation RHS (RHS2) technology built on RNA interference (RNAi) combined with CP4 EPSPS. It utilizes maize endogenous male tissue-specific small interfering RNAs (mts-siRNAs) to trigger cleavage of the CP4 EPSPS mRNA specifically in tassels, resulting in glyphosate-sensitive male cells due to lack of the CP4 EPSPS protein. Male sterility is then induced by glyphosate application at the stages critical for pollen development, and the male-sterile plants are used as the female parent to produce hybrid seed. The endogenous mts-siRNAs are conserved across maize germplasms, and the inducible male sterility was replicated in representative germplasms through introgression of a CP4 EPSPS transgene containing the mts-siRNA target sequence. This technology combines the relative simplicity and convenience of a systemic herbicide spray methodology with targeted protein expression to create an inducible male sterility system for industrial production of row crop hybrid seeds in an environmentally-independent manner.

Development and characterization of the first dsRNA-resistant insect population from western corn rootworm, Diabrotica virgifera virgifera LeConte.

The use of dsRNA to control insect pests via the RNA interference (RNAi) pathway is being explored by researchers globally. However, with every new class of insect control compounds, the evolution of insect resistance needs to be considered, and understanding resistance mechanisms is essential in designing durable technologies and effective resistance management strategies. To gain insight into insect resistance to dsRNA, a field screen with subsequent laboratory selection was used to establish a population of DvSnf7 dsRNA-resistant western corn rootworm, Diabrotica virgifera virgifera, a major maize insect pest. WCR resistant to ingested DvSnf7 dsRNA had impaired luminal uptake and resistance was not DvSnf7 dsRNA-specific, as indicated by cross resistance to all other dsRNAs tested. No resistance to the Bacillus thuringiensis Cry3Bb1 protein was observed. DvSnf7 dsRNA resistance was inherited recessively, located on a single locus, and autosomal. Together these findings will provide insights for dsRNA deployment for insect pest control.

Corn rootworm-active RNA DvSnf7: Repeat dose oral toxicology assessment in support of human and mammalian safety.

Genetically modified (GM) crops have been developed and commercialized that utilize double stranded RNAs (dsRNA) to suppress a target gene(s), producing virus resistance, nutritional and quality traits. MON 87411 is a GM maize variety that leverages dsRNAs to selectively control corn rootworm through production of a 240 base pair (bp) dsRNA fragment targeting for suppression the western corn rootworm (Diabrotica virgifera virgifera) Snf7 gene (DvSnf7). A bioinformatics assessment found that endogenous corn small RNAs matched ∼450 to 2300 unique RNA transcripts that likely code for proteins in rat, mouse, and human, demonstrating safe dsRNA consumption by mammals. Mice were administered DvSnf7 RNA (968 nucleotides, including the 240 bp DvSnf7 dsRNA) at 1, 10, or 100 mg/kg by oral gavage in a 28-day repeat dose toxicity study. No treatment-related effects were observed in body weights, food consumption, clinical observations, clinical chemistry, hematology, gross pathology, or histopathology endpoints. Therefore, the No Observed Adverse Effect Level (NOAEL) for DvSnf7 RNA was 100 mg/kg, the highest dose tested. These results demonstrate that dsRNA for insect control does not produce adverse health effects in mammals at oral doses millions to billions of times higher than anticipated human exposures and therefore poses negligible risk to mammals.

Environmental RNAi in herbivorous insects.

Environmental RNAi (eRNAi) is a sequence-specific regulation of endogenous gene expression in a receptive organism by exogenous double-stranded RNA (dsRNA). Although demonstrated under artificial dietary conditions and via transgenic plant presentations in several herbivorous insects, the magnitude and consequence of exogenous dsRNA uptake and the role of eRNAi remains unknown under natural insect living conditions. Our analysis of coleopteran insects sensitive to eRNAi fed on wild-type plants revealed uptake of plant endogenous long dsRNAs, but not small RNAs. Subsequently, the dsRNAs were processed into 21 nt siRNAs by insects and accumulated in high quantities in insect cells. No accumulation of host plant-derived siRNAs was observed in lepidopteran larvae that are recalcitrant to eRNAi. Stability of ingested dsRNA in coleopteran larval gut followed by uptake and transport from the gut to distal tissues appeared to be enabling factors for eRNAi. Although a relatively large number of distinct coleopteran insect-processed plant-derived siRNAs had sequence complementarity to insect transcripts, the vast majority of the siRNAs were present in relatively low abundance, and RNA-seq analysis did not detect a significant effect of plant-derived siRNAs on insect transcriptome. In summary, we observed a broad genome-wide uptake of plant endogenous dsRNA and subsequent processing of ingested dsRNA into 21 nt siRNAs in eRNAi-sensitive insects under natural feeding conditions. In addition to dsRNA stability in gut lumen and uptake, dosage of siRNAs targeting a given insect transcript is likely an important factor in order to achieve measurable eRNAi-based regulation in eRNAi-competent insects that lack an apparent silencing amplification mechanism.

Small RNA profiles from virus-infected fresh market vegetables.

Functional small RNAs, such as short interfering RNAs (siRNAs) and microRNAs (miRNAs), exist in freshly consumed fruits and vegetables. These siRNAs can be derived either from endogenous sequences or from viruses that infect them. Symptomatic tomatoes, watermelons, zucchini, and onions were purchased from grocery stores and investigated by small RNA sequencing. By aligning the obtained small RNA sequences to sequences of known viruses, four different viruses were identified as infecting these fruits and vegetables. Many of these virally derived small RNAs along with endogenous small RNAs were found to be highly complementary to human genes. However, the established history of safe consumption of these vegetables suggests that this sequence homology has little biological relevance. By extension, these results provide evidence for the safe use by humans and animals of genetically engineered crops using RNA-based suppression technologies, especially vegetable crops with virus resistance conferred by expression of siRNAs or miRNAs derived from viral sequences.

Establishing an in vivo assay system to identify components involved in environmental RNA interference in the western corn rootworm.

The discovery of environmental RNA interference (RNAi), in which gene expression is suppressed via feeding with double-stranded RNA (dsRNA) molecules, opened the door to the practical application of RNAi-based techniques in crop pest management. The western corn rootworm (WCR, Diabrotica virgifera virgifera) is one of the most devastating corn pests in North America. Interestingly, WCR displays a robust environmental RNAi response, raising the possibility of applying an RNAi-based pest management strategy to this pest. Understanding the molecular mechanisms involved in the WCR environmental RNAi process will allow for determining the rate limiting steps involved with dsRNA toxicity and potential dsRNA resistance mechanisms in WCR. In this study, we have established a two-step in vivo assay system, which allows us to evaluate the involvement of genes in environmental RNAi in WCR. We show that laccase 2 and ebony, critical cuticle pigmentation/tanning genes, can be used as marker genes in our assay system, with ebony being a more stable marker to monitor RNAi activity. In addition, we optimized the dsRNA dose and length for the assay, and confirmed that this assay system is sensitive to detect well-known RNAi components such as Dicer-2 and Argonaute-2. We also evaluated two WCR sid1- like (sil) genes with this assay system. This system will be useful to quickly survey candidate systemic RNAi genes in WCR, and also will be adaptable for a genome-wide RNAi screening to give us an unbiased view of the environmental/systemic RNAi pathway in WCR.

Computational sequence analysis of predicted long dsRNA transcriptomes of major crops reveals sequence complementarity with human genes.

Long double-stranded RNAs (long dsRNAs) are precursors for the effector molecules of sequence-specific RNA-based gene silencing in eukaryotes. Plant cells can contain numerous endogenous long dsRNAs. This study demonstrates that such endogenous long dsRNAs in plants have sequence complementarity to human genes. Many of these complementary long dsRNAs have perfect sequence complementarity of at least 21 nucleotides to human genes; enough complementarity to potentially trigger gene silencing in targeted human cells if delivered in functional form. However, the number and diversity of long dsRNA molecules in plant tissue from crops such as lettuce, tomato, corn, soy and rice with complementarity to human genes that have a long history of safe consumption supports a conclusion that long dsRNAs do not present a significant dietary risk.

Analysis of plant-derived miRNAs in animal small RNA datasets.

BACKGROUND: Plants contain significant quantities of small RNAs (sRNAs) derived from various sRNA biogenesis pathways. Many of these sRNAs play regulatory roles in plants. Previous analysis revealed that numerous sRNAs in corn, rice and soybean seeds have high sequence similarity to animal genes. However, exogenous RNA is considered to be unstable within the gastrointestinal tract of many animals, thus limiting potential for any adverse effects from consumption of dietary RNA. A recent paper reported that putative plant miRNAs were detected in animal plasma and serum, presumably acquired through ingestion, and may have a functional impact in the consuming organisms. RESULTS: To address the question of how common this phenomenon could be, we searched for plant miRNAs sequences in public sRNA datasets from various tissues of mammals, chicken and insects. Our analyses revealed that plant miRNAs were present in the animal sRNA datasets, and significantly miR168 was extremely over-represented. Furthermore, all or nearly all (>96%) miR168 sequences were monocot derived for most datasets, including datasets for two insects reared on dicot plants in their respective experiments. To investigate if plant-derived miRNAs, including miR168, could accumulate and move systemically in insects, we conducted insect feeding studies for three insects including corn rootworm, which has been shown to be responsive to plant-produced long double-stranded RNAs. CONCLUSIONS: Our analyses suggest that the observed plant miRNAs in animal sRNA datasets can originate in the process of sequencing, and that accumulation of plant miRNAs via dietary exposure is not universal in animals.

RNA decoys: an emerging component of plant regulatory networks?

The role of non-coding RNAs (ncRNAs), both short and long ncRNAs, in the regulation of gene expression has become evident in recent years. Non-coding RNA-based regulation is achieved through a variety of mechanisms; some are relatively well-characterized, while others are much less understood. MicroRNAs (miRNAs), a class of endogenous small RNAs, function as master regulators of gene expression in eukaryotic organisms. A notable, recently discovered role for long ncRNAs is that of miRNA decoys, also referred to as target mimics or sponges, in which long ncRNAs carry a short stretch of sequence sharing homology to miRNA-binding sites in endogenous targets. As a consequence, miRNA decoys are able to sequester and inactivate miRNA function. Engineered miRNA decoys are also efficacious and useful tools for studying gene function. We recently demonstrated that the potential of miRNA decoys to inactivate miRNAs in the model plants Arabidopsis thaliana and Nicotiana benthamiana is dependent on the level of sequence complementarity to miRNAs of interest. The flexibility of the miRNA decoy approach in sequence-dependent miRNA inactivation, backbone choice, ability to simultaneously inactivate multiple miRNAs, and more importantly, to achieve a desirable level of miRNA inactivation, makes it a potentially useful tool for crop improvement. This research addendum reports the functional extension of miRNA decoys from model plants to crops. Furthermore, endogenous miRNA decoys, first described in plants, have been proposed to play a significant role in regulating the transcriptome in eukaryotes. Using computational analysis, we have identified numerous endogenous sequences with potential miRNA decoy activity for conserved miRNAs in several plant species. Our data suggest that endogenous miRNA decoys can be widespread in plants and may be a component of the global gene expression regulatory network in plants.