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Summary: RNA degradation is a central process required for transcriptional regulation. Eventually, this process degrades diribonucleotides into mononucleotides by specific diribonucleases. In Escherichia coli, oligoribonuclease (Orn) serves this function and is unique as the only essential exoribonuclease. Yet, related organisms, such as Pseudomonas aeruginosa, display a growth defect but are viable without Orn, contesting its essentiality. Here, we take advantage of P. aeruginosa orn mutants to screen for suppressors that restore colony morphology and identified yciV. Purified YciV (RNase AM) exhibits diribonuclease activity. While RNase AM is present in all γ-proteobacteria, phylogenetic analysis reveals differences that map to the active site. RNase AMPa expression in E. coli eliminates the necessity of orn. Together, these results show that diribonuclease activity prevents toxic diribonucleotide accumulation in γ-proteobacteria, suggesting that diribonucleotides may be utilized to monitor RNA degradation efficacy. Because higher eukaryotes encode Orn, these observations indicate a conserved mechanism for monitoring RNA degradation.

Genetic gains made by plant breeders are limited by generational cycling rates and flowering time. Several efforts have been made to reduce the time to switch from vegetative to reproductive stages in plants, but these solutions are usually species-specific and require flowering. The concept of in vitro nurseries is that somatic plant cells can be induced to form haploid cells that have undergone recombination (creating artificial gametes), which can then be used for cell fusion to enable breeding in a Petri dish. The induction of in vitro meiosis, however, is the largest current bottleneck to in vitro nurseries. To help overcome this, we previously described a high-throughput, bi-fluorescent, single cell system in Arabidopsis thaliana, which can be used to test the meiosis-like induction capabilities of candidate factors. In this present work, we validated the system using robust datasets (>4M datapoints) from extensive simulated meiosis induction tests. Additionally, we determined false-detection rates of the fluorescent cells used in this system as well as the ideal tissue source for factor testing.

Abstract Background Strategies to understand meiotic processes have relied on cytogenetic and mutant analysis. However, thus far in vitro meiosis induction is a bottleneck to laboratory-based plant breeding as factor(s) that switch cells in crops species from mitotic to meiotic divisions are unknown. A high-throughput system that allows researchers to screen multiple candidates for their meiotic induction role using low-cost microfluidic devices has the potential to facilitate the identification of factors with the ability to induce haploid cells that have undergone recombination (artificial gametes) in cell cultures. Results A data analysis pipeline and a detailed protocol are presented to screen for plant meiosis induction factors in a quantifiable and efficient manner. We assessed three data analysis techniques using spiked-in protoplast samples (simulated gametes mixed into somatic protoplast populations) of flow cytometry data. Polygonal gating, which was considered the “gold standard”, was compared to two thresholding methods using open-source analysis software. Both thresholding techniques were able to identify significant differences with low spike-in concentrations while also being comparable to polygonal gating. Conclusion Our study provides details to test and analyze candidate meiosis induction factors using available biological resources and open-source programs for thresholding. RFP (PE.CF594.A) and GFP (FITC.A) were the only channels required to make informed decisions on meiosis-like induction and resulted in detection of cell population changes as low as 0.3%, thus enabling this system to be scaled using microfluidic devices at low costs.

Blood flow restriction applied during low-load resistance training (LL-BFR) induces a similar increase in the cross-sectional area of muscle fibers (fCSA) compared to traditional high-load resistance training (HL-RT). However, it is unclear whether LL-BFR leads to differential changes in myofibrillar spacing in muscle fibers and/or extracellular area compared to HL-RT. Therefore, this study aimed to investigate whether the hypertrophy of type I and II fibers induced by LL-BFR or HL-RT is accompanied by differential changes in myofibrillar and non-myofibrillar areas. In addition, we examined if extracellular spacing was differentially affected between these two training protocols. Twenty recreationally active participants were assigned to LL-BFR or HL-RT groups and underwent a 6-week training program. Muscle biopsies were taken before and after the training period. The fCSA of type I and II fibers, the area occupied by myofibrillar and non-myofibrillar components, and extracellular spacing were analyzed using immunohistochemistry techniques. Despite the significant increase in type II and mean (type I + II) fCSA (p < 0.05), there were no significant changes in the proportionality of the myofibrillar and non-myofibrillar areas [∼86% and ∼14%, respectively (p > 0.05)], indicating that initial adaptations to LL-BFR are primarily characterized by conventional hypertrophy rather than disproportionate non-myofibrillar expansion. Additionally, extracellular spacing was not significantly altered between protocols. In summary, our study reveals that LL-BFR, like HL-RT, induces skeletal muscle hypertrophy with proportional changes in the areas occupied by myofibrillar, non-myofibrillar, and extracellular components.

Summary: Peptide-domain interactions mediated by short linear motifs (SLiMs) play crucial roles in cellular biology. The simplicity of SLiMs poses challenges in their computational identification. Existing high-throughput methods for discovering SLiMs lack cellular context as they are typically performed in vitro. We developed a functional selection method using yeast to identify peptides that interact with the endogenous yeast nuclear proteome. Remarkably, peptides selected for in yeast also mediated nuclear import in human cells. Notably, the identified peptides did not resemble classical nuclear localization sequences. This platform has the potential to identify and investigate motifs that interact with the nuclear proteome of yeast and human and to aid in the identification and understanding of alternative protein nuclear import mechanisms. Motivation: Methodologies for identifying short linear motifs have several limitations. Typically, these approaches are limited by scale, making testing of bait and prey libraries in a “many-to-many” fashion impractical. These limitations are further compounded by their in vitro nature and therefore lack functional context. To address these limitations, we have exploited the endogenously expressed yeast nuclear proteome as prey to screen libraries of genetically encoded peptides in an in vivo setting to identify peptide-mediated interactions. This approach capitalizes on the observation that many nuclear proteins lack an identifiable nuclear localization sequence (NLS) and are co-transported into the nucleus via interaction with proteins containing a true NLS.

Abstract Nontuberculous mycobacteria (NTM) are a group of atypical bacteria that may cause a spectrum of clinical manifestations, including pulmonary, musculoskeletal, skin and soft tissue, and cardiac infections. Antimycobacterial medication regimens for NTM infections require multiple agents with prolonged treatment courses and are often associated with poor tolerance in patients and suboptimal clinical outcomes. This review summarizes NTM pharmacotherapy, including treatment concepts, preferred medication regimens according to NTM species and site of infection, and emerging treatment methods for difficult-to-treat species.

Abstract Background Hybridization can be a conservation concern if genomic introgression leads to the loss of an endangered species’ unique genome, or when hybrid offspring are sterile or less fit than their parental species. Yet hybridization can also be an adaptive management tool if rare populations are inbred and have reduced genetic variation, and there is the opportunity to enhance genetic variation through hybridization. The red wolf (Canis rufus) is a critically endangered wolf endemic to the eastern United States, where all extant red wolves are descended from 14 founders which has led to elevated levels of inbreeding over time. Red wolves were considered extirpated from the wild by 1980, but before they disappeared, they interbred with encroaching coyotes creating a genetically admixed population of canids along coastal Texas and Louisiana. In 2018, a genetic study identified individuals on Galveston Island, Texas with significant amounts of red wolf ancestry. We collected 203 fecal samples from Galveston for a more in-depth analysis of this population to identify the amount of red wolf ancestry present and potential mechanisms that support retention of red wolf ancestry on the landscape. Results We identified 24 individual coyotes from Galveston Island and 8 from mainland Texas with greater than 10% red wolf ancestry. Two of those individuals from mainland Texas had greater than 50% red wolf ancestry estimates. Additionally, this population had 5 private alleles that were absent in the North American reference canid populations used in this study, which included 107 southeastern coyotes, 19 captive red wolves, and 38 gray wolves, possibly representing lost red wolf genetic variation. We also identified several individuals on Galveston Island and the mainland of Texas that retained a unique red wolf mitochondrial haplotype present in the red wolf founding population. On Galveston Island, we identified a minimum of four family groups and found coyotes on the island to be highly related, but not genetically depauperate. We did not find clear associations between red wolf ancestry estimates and landscape features, such as open green space or developed areas. Conclusion Our results confirm the presence of substantial red wolf ancestry persisting on Galveston Island and adjacent mainland Texas. This population has the potential to benefit future red wolf conservation efforts through novel reproductive techniques and possibly through de-introgression strategies, with the goals of recovering extinct red wolf genetic variation and reducing inbreeding within the species.

Intravenous push (IVP) antimicrobial administration refers to rapid bolus infusion of medication. This drug delivery method offers improved patient convenience, superior patient and nursing satisfaction, and cost savings when used in outpatient parenteral antimicrobial therapy (OPAT). Antimicrobial agents must demonstrate optimal physiochemical and pharmacologic characteristics, as well as sufficient syringe stability, to be administered in this manner. Additionally, impacts on medication tolerability, patient safety, and effectiveness must be considered. This narrative review summarizes the available data and practical implications of IVP administration of antimicrobials in the OPAT setting.

Efforts to increase genetic gains in breeding programs of flowering plants depend on making genetic crosses. Time to flowering, which can take months to decades depending on the species, can be a limiting factor in such breeding programs. It has been proposed that the rate of genetic gain can be increased by reducing the time between generations by circumventing flowering through the in vitro induction of meiosis. In this review, we assess technologies and approaches that may offer a path towards meiosis induction, the largest current bottleneck for in vitro plant breeding. Studies in non-plant, eukaryotic organisms indicate that the in vitro switch from mitotic cell division to meiosis is inefficient and occurs at very low rates. Yet, this has been achieved with mammalian cells by the manipulation of a limited number of genes. Therefore, to experimentally identify factors that switch mitosis to meiosis in plants, it is necessary to develop a high-throughput system to evaluate a large number of candidate genes and treatments, each using large numbers of cells, few of which may gain the ability to induce meiosis.

Abstract Background Preclinical studies and early clinical trials have shown that targeting cancer neoantigens is a promising approach towards the development of personalized cancer immunotherapies. DNA vaccines can be rapidly and efficiently manufactured and can integrate multiple neoantigens simultaneously. We therefore sought to optimize the design of polyepitope DNA vaccines and test optimized polyepitope neoantigen DNA vaccines in preclinical models and in clinical translation. Methods We developed and optimized a DNA vaccine platform to target multiple neoantigens. The polyepitope DNA vaccine platform was first optimized using model antigens in vitro and in vivo. We then identified neoantigens in preclinical breast cancer models through genome sequencing and in silico neoantigen prediction pipelines. Optimized polyepitope neoantigen DNA vaccines specific for the murine breast tumor E0771 and 4T1 were designed and their immunogenicity was tested in vivo. We also tested an optimized polyepitope neoantigen DNA vaccine in a patient with metastatic pancreatic neuroendocrine tumor. Results Our data support an optimized polyepitope neoantigen DNA vaccine design encoding long (≥20-mer) epitopes with a mutant form of ubiquitin (Ubmut) fused to the N-terminus for antigen processing and presentation. Optimized polyepitope neoantigen DNA vaccines were immunogenic and generated robust neoantigen-specific immune responses in mice. The magnitude of immune responses generated by optimized polyepitope neoantigen DNA vaccines was similar to that of synthetic long peptide vaccines specific for the same neoantigens. When combined with immune checkpoint blockade therapy, optimized polyepitope neoantigen DNA vaccines were capable of inducing antitumor immunity in preclinical models. Immune monitoring data suggest that optimized polyepitope neoantigen DNA vaccines are capable of inducing neoantigen-specific T cell responses in a patient with metastatic pancreatic neuroendocrine tumor. Conclusions We have developed and optimized a novel polyepitope neoantigen DNA vaccine platform that can target multiple neoantigens and induce antitumor immune responses in preclinical models and neoantigen-specific responses in clinical translation.

People Living with HIV (PLWH) remain disproportionately susceptible to vaccine-preventable illnesses due to increased morbidity and mortality from common pathogens, increased transmission related to epidemiologic factors, and decreased vaccination rates. We aimed to describe patient-specific predictive factors that may impact adherence to the CDC’s recommended vaccination schedules in PLWH. We retrospectively evaluated adult PLWH in care at the University of Nebraska Medical Center’s HIV clinic and collected information related to demographics, clinic visits, vaccination status, and measures of HIV disease control. Patients were categorized as “Adherent” if they had received all vaccinations for which they were eligible and were categorized as “Non-Adherent” if they were deficient or delayed in receiving one or more vaccinations. Participant characteristics were compared between groups by multivariable logistic regression to identify predictors associated with vaccine schedule non-adherence. We evaluated 502 PLWH who met our inclusion criteria; 206 of these (41%) had received all eligible vaccinations, while 296 (59%) were missing one or more vaccinations. The mean age of participants was 48 years old, 76% were male, and 53% were white. Our participants had a median of 2.83 clinic visits per year and missed 8.3% of scheduled clinic visits. Factors associated with non-adherence to vaccination schedules included a high frequency of missed clinic appointments (>10%), men who have sex with men, and a CD4 count

Online instructional design and how to engage students cognitively in online asynchronous courses have been an ongoing question. This case study presents an intentional design of an asynchronous online graduate course to foster cognitive presence. The research questions investigate students’ cognitive presence (CP) captured by two measures: Community of Inquiry (CoI) survey (for self-report) and Linguistic Inquiry and Word Count (LIWC) software (for actual behaviors) in this online course. Additionally, it also addresses how cognitive presence is related to other presences and how the online course design elements were perceived by students. Results showed that students perceived high levels of cognitive presence and they showed high cognitive presence in their discussion board acts. There was a relationship between three presences; and findings showed that teacher and social presence were strong predictors of perceived cognitive presence. Although students in the study rated themselves high on the CoI instrument and scored high on the LIWC for cognitive presence, self-presentation bias still emerged. Strategies that helped students to stay cognitively present in this asynchronous online course included: instructor responsiveness in discussion posts and creating dialogue, creating course assignments as online hands-on project, interviewing guest speakers on specific course topics, weekly recap and orientation videos, feedback, case-based discussions, and other elements.

Papillomaviruses, polyomaviruses and adenoviruses are collectively categorized as the small DNA tumour viruses. Notably, human adenoviruses were the first human viruses demonstrated to be able to cause cancer, albeit in non-human animal models. Despite their long history, no human adenovirus is a known causative agent of human cancers, unlike a subset of their more famous cousins, including human papillomaviruses and human Merkel cell polyomavirus. Nevertheless, seminal research using human adenoviruses has been highly informative in understanding the basics of cell cycle control, gene expression, apoptosis and cell differentiation. This review highlights the contributions of human adenovirus research in advancing our knowledge of the molecular basis of cancer.

Cervical cancer (CC) is the second most common cancer in women worldwide and the fourth leading cause of cancer-associated death in women. Although human papillomavirus (HPV) infection is associated with nearly all CC, it has recently become clear that HPV−negative (HPV−) CC represents a distinct disease phenotype with increased mortality. HPV−positive (HPV+) and HPV− CC demonstrate different molecular pathology, prognosis, and response to treatment. Furthermore, CC caused by HPV α9 types (HPV16-like) often have better outcomes than those caused by HPV α7 types (HPV18-like). This study systematically and comprehensively compared the expression of genes involved in major histocompatibility complex (MHC) class I and II presentation within CC caused by HPV α9 types, HPV α7 types, and HPV− CC. We observed increased expression of MHC class I and II classical and non-classical genes in HPV+ CC and overall higher expression of genes involved in their antigen loading and presentation apparatus as well as transcriptional regulation. Increased expression of MHC I-related genes differs from previous studies using cell culture models. These findings identify crucial differences between antigen presentation within the tumor immune microenvironments of HPV+ and HPV− CC, as well as modest differences between HPV α9 and α7 CC. These differences may contribute to the altered patient outcomes and responses to immunotherapy observed between these distinct cancers.

PurposeClinical evidence suggests radiation induces changes in the brain microenvironment that affect subsequent response to treatment. This study investigates the effect of previous radiation, delivered six weeks prior to orthotopic tumor implantation, on subsequent tumor growth and therapeutic response to anti-PD-L1 therapy in an intracranial mouse model, termed the Radiation Induced Immunosuppressive Microenvironment (RI2M) model.Method and MaterialsC57Bl/6 mice received focal (hemispheric) single-fraction, 30-Gy radiation using the Leksell GammaKnife® Perfexion™, a dose that does not produce frank/gross radiation necrosis. Non-irradiated GL261 glioblastoma tumor cells were implanted six weeks later into the irradiated hemisphere. Lesion volume was measured longitudinally by in vivo MRI. In a separate experiment, tumors were implanted into either previously irradiated (30 Gy) or non-irradiated mouse brain, mice were treated with anti-PD-L1 antibody, and Kaplan-Meier survival curves were constructed. Mouse brains were assessed by conventional hematoxylin and eosin (H&E) staining, IBA-1 staining, which detects activated microglia and macrophages, and fluorescence-activated cell sorting (FACS) analysis.ResultsTumors in previously irradiated brain display aggressive, invasive growth, characterized by viable tumor and large regions of hemorrhage and necrosis. Mice challenged intracranially with GL261 six weeks after prior intracranial irradiation are unresponsive to anti-PD-L1 therapy. K-M curves demonstrate a statistically significant difference in survival for tumor-bearing mice treated with anti-PD-L1 antibody between RI2M vs. non-irradiated mice. The most prominent immunologic change in the post-irradiated brain parenchyma is an increased frequency of activated microglia.ConclusionsThe RI2M model focuses on the persisting (weeks-to-months) impact of radiation applied to normal, control-state brain on the growth characteristics and immunotherapy response of subsequently implanted tumor. GL261 tumors growing in the RI2M grew markedly more aggressively, with tumor cells admixed with regions of hemorrhage and necrosis, and showed a dramatic loss of response to anti-PD-L1 therapy compared to tumors in non-irradiated brain. IHC and FACS analyses demonstrate increased frequency of activated microglia, which correlates with loss of sensitivity to checkpoint immunotherapy. Given that standard-of-care for primary brain tumor following resection includes concurrent radiation and chemotherapy, these striking observations strongly motivate detailed assessment of the late effects of the RI2M on tumor growth and therapeutic efficacy.

Lakeshore areas provide important habitat for aquatic invertebrates in shallow lakes. However, these zones are prone to anthropogenic disturbances that include shoreline development, urbanization, nutrient inputs, agricultural and(or) recreational use. Among recreational uses, public access sites are often developed to accommodate boaters and facilitate lake access via boat ramps. Although the ‘foot print’ associated with boat ramp structures can be relatively small compared to total shoreline coverage, little is known about the relative effects of boating activity on littoral zones and macroinvertebrate communities. In this study, we assess the relative impact of boating-related activities on aquatic macroinvertebrate communities at high-use (primary) and low-use (secondary) boat ramps on five glacial lakes of eastern South Dakota. Macroinvertebrate assemblages were dominated by few taxa that included Chironomidae, Corixidae, Caenidae, and Amphipoda. Moreover, boat ramp use did not influence abundance or diversity of aquatic macroinvertebrates. Habitat, specifically substrate composition, was also similar between primary and secondary boat ramps despite more intense use associated with primary boat ramps. Our results support related findings that aquatic invertebrate assemblages in the Prairie Pothole Region are structured by regional environmental variability (climate, habitat, and water quality) resulting in communities with characteristically low diversity and tolerant taxa. This may explain why small-scale disturbance associated with boating activity has no discernable effect on macroinvertebrate assemblages in glacial lakes of the Prairie Pothole Region.

The introduction of flathead catfish (Pylodictis olivaris) into Lake Mitchell presented a unique opportunity to study the population dynamics of this species in a South Dakota impoundment. We collected flathead catfish using daytime, low-frequency electrofishing during June 2013, 2014, and 2015 and July, August and October of 2014 to examine population characteristics including abundance, recruitment, mortality, growth, condition, and diet. The flathead catfish population in Lake Mitchell was estimated at 1348 individuals (95% CI = 459–1455; density = 4.97/ha) in 2014 and 1197 individuals (95% CI = 931–1461; density = 4.42/ha) in 2015. Individuals from 11 year classes ranging from 1 to 13 years old were present. The population exhibited consistent recruitment, and annual mortality was estimated at 39%. Flathead catfish grew quickly exceeding stock length at age 3 and quality length at age 5; however, growth slowed in 2015. Similarly, condition of substock and stock-quality length fish declined in 2014 and 2015, respectively. The decline in growth and condition coincided with the recruitment of a large 2012 year class and may be an early indicator of intraspecific competition. Diets of Lake Mitchell flathead catfish primarily consisted of crayfish (Orconectes spp.) and fish with flathead catfish shifting to piscivory at approximately 400 mm. The high percentage of centrarchids in flathead catfish diets along with an increase in flathead catfish abundance coinciding with a decrease in bluegill abundance may indicate that flathead catfish are negatively impacting the bluegill population in Lake Mitchell.

Neoantigens represent promising targets for personalized cancer vaccine strategies. However, the feasibility of this approach in lower mutational burden tumors like glioblastoma (GBM) remains unknown. We have previously reported the use of an immunogenomics pipeline to identify candidate neoantigens in preclinical models of GBM. Here, we report the application of the same immunogenomics pipeline to identify candidate neoantigens and guide screening for neoantigen-specific T cell responses in a patient with GBM treated with a personalized synthetic long peptide vaccine following autologous tumor lysate DC vaccination. Following vaccination, reactivity to three HLA class I- and five HLA class II-restricted candidate neoantigens were detected by IFN-γ ELISPOT in peripheral blood. A similar pattern of reactivity was observed among isolated post-treatment tumor-infiltrating lymphocytes. Genomic analysis of pre- and post-treatment GBM reflected clonal remodeling. These data demonstrate the feasibility and translational potential of a therapeutic neoantigen-based vaccine approach in patients with primary CNS tumors.

ABSTRACT IMPACT: We seek to determine which lymph nodes drain the human brain. OBJECTIVES/GOALS: Lymphatic vessels train lymphatic fluid from the central nervous system (CNS), but the specific lymph nodes that these vessels drain to remains unknown in humans. We intend on using technetium tilmanocept (TcTM)to map the draining lymph nodes of the CNSin humans. METHODS/STUDY POPULATION: Patients having a tumor resected are eligible for the trial. All patients will have TcTM injected intracranially after tumor resection. Six patients will be enrolled in Cohort 1 to define the time course of drainage to the lymph nodes. Patients in Cohort 1 will be imaged with planar LS within 7 hours of injection and the following day. Either 12 or 24 patients will be enrolled into Cohort 2 to localize the draining lymph nodes with SPECT-CT. The optimal imaging timepoint from Cohort 1 will be used for Cohort 2. Patients in Cohort 2 will be stratified depending on if their tumor is in the frontal, parietal, occipital, or temporal lobe. RESULTS/ANTICIPATED RESULTS: We anticipate that we will detect TcTMin the deep cervical lymph nodes after injection into the brain. It is unclear exactly which lymph nodes the tracer will go to. We hypothesize that the results among patients will be similar, but interindividual variation is a possibility. Furthermore, patients with disease in different lobes of the brain may have different lymph drainage patterns. DISCUSSION/SIGNIFICANCE OF FINDINGS: We seek to answer a fundamental question of human anatomy: what lymph nodes drain the human brain? Additionally, knowing which nodes drain the human brain could shape future research of immunotherapy in patients with brain cancer or autoimmune disease such as multiple sclerosis.

Background: Glioblastoma multiforme is a malignant intracranial neoplasm that constitutes a therapeutic challenge because of the associated high morbidity and mortality given the lack of effective approved medication and aggressive nature of the tumor. However, there has been extensive research recently to address the reasons implicated in the resistant nature of the tumor to pharmaceutical compounds, which have resulted in several clinical trials investigating promising treatment approaches. Methods: We reviewed literature published since 2010 from PUBMED and several annual meeting abstracts through 15 September 2020. Selected articles included those relevant to topics of glioblastoma tumor biology, original basic research, clinical trials, seminal reviews, and meta-analyses. We provide a discussion based on the collected evidence regarding the challenging factors encountered during treatment, and we highlighted the relevant trials of novel therapies including immunotherapy and targeted medication. Results: Selected literature revealed four main factors implicated in the low efficacy encountered with investigational treatments which included: (1) blood-brain barrier; (2) immunosuppressive microenvironment; (3) genetic heterogeneity; (4) external factors related to previous systemic treatment that can modulate tumor microenvironment. Investigational therapies discussed in this review were classified as immunotherapy and targeted therapy. Immunotherapy included: (1) immune checkpoint inhibitors; (2) adoptive cell transfer therapy; (3) therapeutic vaccines; (4) oncolytic virus therapy. Targeted therapy included tyrosine kinase inhibitors and other receptor inhibitors. Finally, we provide our perspective on future directions in treatment of glioblastoma. Conclusion: Despite the limited success in development of effective therapeutics in glioblastoma, many treatment approaches hold potential promise including immunotherapy and novel combinational drugs. Addressing the molecular landscape and resistant immunosuppressive nature of glioblastoma are imperative in further development of effective treatments.

One of the most conserved cellular pathways among eukaryotes is the extensively studied classical protein nuclear import pathway mediated by importin-α. Classical nuclear localization signals (cNLSs) are recognized by importin-α and are highly predictable due to their abundance of basic amino acids. However, various studies in model organisms have repeatedly demonstrated that only a fraction of nuclear proteins contain identifiable cNLSs, including those that directly interact with importin-α. Using data from the Human Protein Atlas and the Human Reference Interactome, and proteomic data from BioID/protein-proximity labeling studies using multiple human importin-α proteins, we determine that nearly 50% of the human nuclear proteome does not have a predictable cNLS. Surprisingly, between 25% and 50% of previously identified human importin-α cargoes do not have predictable cNLS. Analysis of importin-α cargo without a cNLS identified an alternative basic rich motif that does not resemble a cNLS. Furthermore, several previously suspected piggybacking proteins were identified, such as those belonging to the RNA polymerase II and transcription factor II D complexes. Additionally, many components of the mediator complex interact with at least one importin-α, yet do not have a predictable cNLS, suggesting that many of the subunits may enter the nucleus through an importin-α-dependent piggybacking mechanism.

Epstein−Barr virus (EBV) is responsible for approximately 9% of stomach adenocarcinomas. EBV-encoded microRNAs have been reported as reducing the function of the class I major histocompatibility complex (MHC-I) antigen presentation apparatus, which could allow infected cells to evade adaptive immune responses. Using data from nearly 400 human gastric carcinomas (GCs), we assessed the impact of EBV on MHC-I heavy and light chain mRNA levels, as well as multiple other components essential for antigen processing and presentation. Unexpectedly, mRNA levels of these genes were as high, or higher, in EBV-associated gastric carcinomas (EBVaGCs) compared to normal control tissues or other GC subtypes. This coordinated upregulation could have been a consequence of the higher intratumoral levels of interferon γ in EBVaGCs, which correlated with signatures of increased infiltration by T and natural killer (NK) cells. These results indicate that EBV-encoded products do not effectively reduce mRNA levels of the MHC-I antigen presentation apparatus in human GCs.

ABSTRACT As obligate intracellular parasites, viruses are dependent on their infected hosts for survival. Consequently, viruses are under enormous selective pressure to utilize available cellular components and processes to their own advantage. As most, if not all, cellular activities are regulated at some level via protein interactions, host protein interaction networks are particularly vulnerable to viral exploitation. Indeed, viral proteins frequently target highly connected “hub” proteins to “hack” the cellular network, defining the molecular basis for viral control over the host. This widespread and successful strategy of network intrusion and exploitation has evolved convergently among numerous genetically distinct viruses as a result of the endless evolutionary arms race between pathogens and hosts. Here we examine the means by which a particularly well-connected viral hub protein, human adenovirus E1A, compromises and exploits the vulnerabilities of eukaryotic protein interaction networks. Importantly, these interactions identify critical regulatory hubs in the human proteome and help define the molecular basis of their function.

Protein nuclear transport is an integral process to many cellular pathways and often plays a critical role during viral infection. To overcome the barrier presented by the nuclear membrane and gain access to the nucleus, virally encoded proteins have evolved ways to appropriate components of the nuclear transport machinery. By binding karyopherins, or the nuclear pore complex, viral proteins influence their own transport as well as the transport of key cellular regulatory proteins. This review covers how viral proteins can interact with different components of the nuclear import machinery and how this influences viral replicative cycles. We also highlight the effects that viral perturbation of nuclear transport has on the infected host and how we can exploit viruses as tools to study novel mechanisms of protein nuclear import. Finally, we discuss the possibility that drugs targeting these transport pathways could be repurposed for treating viral infections.

Online instructional design and how to engage students cognitively in online asynchronous courses have been an ongoing question. This case study presents an intentional design of an asynchronous online graduate course to foster cognitive presence. The research questions investigate students' cognitive presence (CP) captured by two measures: Community of Inquiry (CoI) survey (for self-report) and Linguistic Inquiry and Word Count (LIWC) software (for actual behaviors) in this online course. Additionally, it also addresses how cognitive presence is related to other presences and how the online course design elements were perceived by students. Results showed that students perceived high levels of cognitive presence and they showed high cognitive presence in their discussion board acts. There was a relationship between three presences; and findings showed that teacher and social presence were strong predictors of perceived cognitive presence. Although students in the study rated themselves high on the CoI instrument and scored high on the LIWC for cognitive presence, self-presentation bias still emerged. Strategies that helped students to stay cognitively present in this asynchronous online course included: instructor responsiveness in discussion posts and creating dialogue, creating course assignments as online hands-on project, interviewing guest speakers on specific course topics, weekly recap and orientation videos, feedback, case-based discussions, and other elements.

Encouraging teachers to reflect on their instructional practices and course design has been shown to be an effective means of improving instruction and student learning. However, the process of encouraging reflection is difficult; reflection requires quality data, thoughtful analysis, and contextualized interpretation. Because of this, research on and the practice of reflection is often limited to pre-service training or short professional development cycles. This study explores how natural language processing, deep-learning methods can be used to support continuous teacher reflection by facilitating data collection and analysis in any instructional setting that includes ample linguistic and assessment material. Data was collected from an existing introductory undergraduate biology course. A Bidirectional Long-Short Term Memory network was trained to predict assessment item difficulty and tasked with assigning difficulty to recorded lectures. Comparison with the instructor's perceptions of lecture material difficulty suggested the model was highly reliable at predicting difficult lecture material. We discuss how this model could be expanded into an AI toolkit meant to aid in teacher reflection on their practices and curriculum.

Early region 1A (E1A) is the first viral protein produced upon human adenovirus (HAdV) infection. This multifunctional protein transcriptionally activates other HAdV early genes and reprograms gene expression in host cells to support productive infection. E1A functions by interacting with key cellular regulatory proteins through short linear motifs (SLiMs). In this study, the molecular determinants of interaction between E1A and BS69, a cellular repressor that negatively regulates E1A transactivation, were systematically defined by mutagenesis experiments. We found that a minimal sequence comprised of MPNLVPEV, which contains a conserved PXLXP motif and spans residues 112⁻119 in HAdV-C5 E1A, was necessary and sufficient in binding to the myeloid, Nervy, and DEAF-1 (MYND) domain of BS69. Our study also identified residues P113 and L115 as critical for this interaction. Furthermore, the HAdV-C5 and -A12 E1A proteins from species C and A bound BS69, but those of HAdV-B3, -E4, -D9, -F40, and -G52 from species B, E, D, F, and G, respectively, did not. In addition, BS69 functioned as a repressor of E1A-mediated transactivation, but only for HAdV-C5 and HAdV-A12 E1A. Thus, the PXLXP motif present in a subset of HAdV E1A proteins confers interaction with BS69, which serves as a negative regulator of E1A mediated transcriptional activation.

Neoantigens are tumor-specific peptide sequences resulting from sources such as somatic DNA mutations. Upon loading onto major histocompatibility complex (MHC) molecules, they can trigger recognition by T cells. Accurate neoantigen identification is thus critical for both designing cancer vaccines and predicting response to immunotherapies. Neoantigen identification and prioritization relies on correctly predicting whether the presenting peptide sequence can successfully induce an immune response. Because most somatic mutations are single-nucleotide variants, changes between wild-type and mutated peptides are typically subtle and require cautious interpretation. A potentially underappreciated variable in neoantigen prediction pipelines is the mutation position within the peptide relative to its anchor positions for the patient's specific MHC molecules. Whereas a subset of peptide positions are presented to the T cell receptor for recognition, others are responsible for anchoring to the MHC, making these positional considerations critical for predicting T cell responses. We computationally predicted anchor positions for different peptide lengths for 328 common HLA alleles and identified unique anchoring patterns among them. Analysis of 923 tumor samples shows that 6 to 38% of neoantigen candidates are potentially misclassified and can be rescued using allele-specific knowledge of anchor positions. A subset of anchor results were orthogonally validated using protein crystallography structures. Representative anchor trends were experimentally validated using peptide-MHC stability assays and competition binding assays. By incorporating our anchor prediction results into neoantigen prediction pipelines, we hope to formalize, streamline, and improve the identification process for relevant clinical studies.

This exploratory paper highlights how problem-based learning (PBL) provided the pedagogical framework used to design and interpret learning analytics from "Crystal Island: EcoJourneys," a collaborative game-based learning environment centred on supporting science inquiry. In "Crystal Island: EcoJourneys," students work in teams of four, investigate the problem individually and then utilize a brainstorming board, an in-game PBL whiteboard that structured the collaborative inquiry process. The paper addresses a central question: how can PBL support the interpretation of the observed patterns in individual actions and collaborative interactions in the collaborative game-based learning environment? Drawing on a mixed method approach, we first analyzed students' pre- and post-test results to determine if there were learning gains. We then used principal component analysis (PCA) to describe the patterns in game interaction data and clustered students based on the PCA. Based on the pre- and post-test results and PCA clusters, we used interaction analysis to understand how collaborative interactions unfolded across selected groups. Results showed that students learned the targeted content after engaging with the game-based learning environment. Clusters based on the PCA revealed four main ways of engaging in the game-based learning environment: students engaged in low to moderate self-directed actions with: (1) high and (2) moderate collaborative sense-making actions; (3) low self-directed with low collaborative sense-making actions; and (4) high self-directed actions with low collaborative sense-making actions. Qualitative interaction analysis revealed that a key difference among four groups in each cluster was the nature of verbal student discourse: students in the low to moderate self-directed and high collaborative sense-making cluster actively initiated discussions and integrated information they learned to the problem, whereas students in the other clusters required more support. These findings have implications for designing adaptive support that responds to students' interactions with in-game activities.

Interested in the absolute preservation rate of one of the best understood dinosaurs, Tyrannosaurus rex, Marshall et al. (2021) estimated the total number that ever lived.  This required estimating its geographic range, longevity, and population density, which required estimating its body mass and physiology.  Meiri (2021) questions the precision of our estimates, emphasizing the difficulties in estimating population densities and geographic ranges for living species, and in error propagation.  He posits that estimating population sizes of extinct species is ‘extremely unlikely’.  While we agree that we did not quantify some sources of uncertainty (for example, in the physiology of T. rex), our calculations do not depend on short-term changes in population density and geographic range, but rather on their long-term averages, rendering many of Meiri’s (2021) concerns moot.  We also note that Monte Carlo Simulation propagates uncertainties robustly.  That is, we feel we have, in fact, developed a general method for estimating population sizes for extinct species, regardless of any shortfalls in implementation.

Porous, stacked two-dimensional covalent organic frameworks (2D COFs) bearing semiconducting linkers can support directional charge transfer across adjacent layers of the COF. To better inform the current and possible future design rules for enhancing electron and hole transport in such materials, an understanding of how linker selection and functionalization affects interlayer electronic couplings is essential. We report electronic structure simulation and analysis of electronic couplings across adjacent linker units and to encapsulated species in functionalized electroactive 2D COFs. The detailed dependence of these electronic couplings on interlayer interactions is examined through scans along key interlayer degrees of freedom and through configurational sampling from equilibrium molecular dynamics on semiempirical potential energy surfaces. Beyond affirming the sensitivity of the electronic coupling to interlayer distance and orientation, these studies offer guidance toward linker functionalization strategies for enhancing charge carrier transport in electroactive 2D COFs. [ABSTRACT FROM AUTHOR]