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Thousands of outer-arm dyneins (OADs) are arrayed in the axoneme to drive a rhythmic ciliary beat. Coordination among multiple OADs is essential for generating mechanical forces to bend microtubule doublets (MTDs). Using electron microscopy, we determined high-resolution structures of Tetrahymena thermophila OAD arrays bound to MTDs in two different states. OAD preferentially binds to MTD protofilaments with a pattern resembling the native tracks for its distinct microtubule-binding domains. Upon MTD binding, free OADs are induced to adopt a stable parallel conformation, primed for array formation. Extensive tail-to-head (TTH) interactions between OADs are observed, which need to be broken for ATP turnover by the dynein motor. We propose that OADs in an array sequentially hydrolyze ATP to slide the MTDs. ATP hydrolysis in turn relaxes the TTH interfaces to effect free nucleotide cycles of downstream OADs. These findings lead to a model explaining how conformational changes in the axoneme produce coordinated action of dyneins.

Reconstruction of the anisotropic structure and proper function of the knee meniscus remains an important challenge to overcome, because the complexity of the zonal tissue organization in the meniscus has important roles in load bearing and shock absorption. Current tissue engineering solutions for meniscus reconstruction have failed to achieve and maintain the proper function in vivo because they have generated homogeneous tissues, leading to long-term joint degeneration. To address this challenge, we applied biomechanical and biochemical stimuli to mesenchymal stem cells seeded into a biomimetic scaffold to induce spatial regulation of fibrochondrocyte differentiation, resulting in physiological anisotropy in the engineered meniscus. Using a customized dynamic tension-compression loading system in conjunction with two growth factors, we induced zonal, layer-specific expression of type I and type II collagens with similar structure and function to those present in the native meniscus tissue. Engineered meniscus demonstrated long-term chondroprotection of the knee joint in a rabbit model. This study simultaneously applied biomechanical, biochemical, and structural cues to achieve anisotropic reconstruction of the meniscus, demonstrating the utility of anisotropic engineered meniscus for long-term knee chondroprotection in vivo.

The hepatic growth hormone (GH)-insulin-like growth factor (IGF)-I axis is essential for regulating intrahepatic lipid metabolism. Ketotic cows are characterized by high blood concentrations of fatty acids and β-hydroxybutyrate (BHB), which display lipotoxicity. The aim of this study was to investigate changes in the hepatic GH-IGF-I axis in ketotic cows and to determine the effects of fatty acids and BHB on the GH-IGF-I axis in calf hepatocytes. Liver and blood samples were collected from healthy (n = 15) and clinically ketotic (n = 15) cows. Hepatocytes were isolated from calves and treated with various concentrations of GH, fatty acids, and BHB. The results showed that clinically ketotic cows displayed a high blood concentration of GH, a low blood concentration of IGF-I, and decreased hepatic GHR1A expression as well as impaired hepatic Janus kinase 2 (JAK2)-signal transducer and activator of transcription 5 (STAT5) signaling. In vitro, GH treatment induced activation of the JAK2-STAT5 pathway to increase the mRNA expression and secretion of IGF-I in calf hepatocytes. More importantly, treatment with fatty acids or BHB significantly inhibited GHR1A mRNA and JAK2 protein expression, as well as the STAT5 phosphorylation level and phospho-STAT5 nuclear translocation; these effects markedly reduced IGF1 mRNA expression and secretion in calf hepatocytes. In summary, these results indicate that high blood concentrations of fatty acids or BHB can impair the intrahepatic GH-mediated JAK2-STAT5 pathway and downregulate IGF-I expression and secretion in ketotic cows.

There is growing interest in the use of nonmodel microorganisms as hosts for biopharmaceutical manufacturing. These hosts require genomic engineering to meet clinically relevant product qualities and titers, but the adaptation of tools for editing genomes, such as CRISPR-Cas9, has been slow for poorly characterized hosts. Specifically, a lack of biochemical characterization of RNA polymerase III transcription has hindered reliable expression of guide RNAs in new hosts. Here, we present a sequencingbased strategy for the design of host-specific cassettes for modular, reliable, expression of guide RNAs. Using this strategy, we achieved up to 95% gene editing efficiency in the methylotrophic yeast Komagataella phaff ii. We applied this approach for the rapid, multiplexed engineering of a complex phenotype, achieving humanized product glycosylation in two sequential steps of engineering. Reliable extension of simple gene editing tools to nonmodel manufacturing hosts will enable rapid engineering of manufacturing strains tuned for specific product profiles and potentially decrease the costs and timelines for process development.

The inevitable deficiency in nutrients and energy at the onset of lactation requires an optimal adaptation of the hepatic metabolism to overcome metabolic stress. Fatty liver is one of the main health disorders after parturition. Therefore, to investigate changes in hepatic lipid metabolic status and mitochondria in dairy cows with mild fatty liver, liver and blood samples were collected from healthy cows (n = 15) and cows with mild fatty liver (n = 15). To determine the effects of palmitic acids (PA), one of the major component of fatty acids, on lipid metabolism and mitochondria in vitro, calf hepatocytes were isolated from healthy calves and treated with various concentrations of PA (0, 50, 100, and 200 μM). Dairy cows with mild fatty liver displayed hepatic lipid accumulation. The protein levels of sterol regulatory element-binding protein 1c (SREBP-1c) and peroxisome proliferator-activated receptor-α (PPARα) and mRNA levels of acetyl CoA carboxylase 1 (ACC1), fatty acid synthase (FAS), acyl-CoA oxidase (ACO), and carnitine palmitoyltransferase 1A (CPT1A) were significantly higher in dairy cows with mild fatty liver than in control cows. The hepatic mitochondrial DNA content, mRNA levels of oxidative phosphorylation complexes I to V (CO 1-V), protein levels of cytochrome c oxidase subunit IV (COX IV), voltage dependent anion channel 1 (VDAC1), peroxisome proliferator activated receptor-γ coactivator-1α (PGC-1α) and nuclear respiratory factor 1 (NRF1), and adenosine triphosphate (ATP) content were all markedly increased in the liver of dairy cows with mild fatty liver compared with healthy cows. The PA treatment significantly increased lipid accumulation; protein levels of SREBP-1c and PPARα; and mRNA levels of ACC1, FAS, ACO, and CPT1A in calf hepatocytes. Moreover, the mitochondrial DNA content, mRNA levels of CO 1-V, protein levels of COX IV, VDAC1, PGC-1α, NRF1, mitochondrial transcription factor A, and ATP content were significantly increased in PA-treated hepatocytes compared with control hepatocytes. The protein level of mitofusin-2 was significantly decreased in PA-treated groups. In conclusion, lipid synthesis and oxidation, number of mitochondria, and ATP production were increased in the liver of dairy cows with mild fatty liver and PA-treated calf hepatocytes. These changes in hepatic mitochondria and lipid metabolism may be the adaptive mechanism of dairy cows with mild fatty liver.

Background: MicroRNAs (miRNAs) are a set of small non-coding RNAs serving as important negative gene regulators. In animals, miRNAs turn down protein translation by binding to the 3' UTR regions of target genes with imperfect complementary pairing. The identification of microRNA targets has become one of the major challenges of miRNA research. Bioinformatics investigations on miRNA target have resulted in a number of target prediction tools. Although these tools are capable of predicting hundreds of targets for a given miRNA, many of them suffer from high false positive rates, indicating the need for a post-processing filter for the predicted targets. Once trained with experimentally validated true and false targets, machine learning methods appear to be ideal approaches to distinguish the true targets from the false ones.