There are many proteomic applications that require large collections of purified protein, but parallel production of large numbers of different proteins remains a very challenging task. To help meet the needs of the scientific community, we have developed a human protein production pipeline. Using high-throughput (HT) methods, we transferred the genes of 31 full-length proteins into three expression vectors, and expressed the collection as N-terminal HaloTag fusion proteins in Escherichia coli and two commercial cell-free (CF) systems, wheat germ extract (WGE) and HeLa cell extract (HCE). Expression was assessed by labeling the fusion proteins specifically and covalently with a fluorescent HaloTag ligand and detecting its fluorescence on a LabChip[superscript ®] GX microfluidic capillary gel electrophoresis instrument. This automated, HT assay provided both qualitative and quantitative assessment of recombinant protein. E. coli was only capable of expressing 20% of the test collection in the supernatant fraction with ≥20 μg yields, whereas CF systems had ≥83% success rates. We purified expressed proteins using an automated HaloTag purification method. We purified 20, 33, and 42% of the test collection from E. coli, WGE, and HCE, respectively, with yields ≥1 μg and ≥90% purity. Based on these observations, we have developed a triage strategy for producing full-length human proteins in these three expression systems.

Pathogen reduction is a viable approach to ensure the continued safety of the blood supply against emerging pathogens. However, the currently licensed pathogen reduction techniques are ineffective against non-enveloped viruses such as hepatitis A virus, and they introduce chemicals with concerns of side effects which prevent their widespread use. In this report, we demonstrate the inactivation of both enveloped and non-enveloped viruses in human plasma using a novel chemical-free method, a visible ultrashort pulsed laser. We found that laser treatment resulted in 2-log, 1-log, and 3-log reductions in human immunodeficiency virus, hepatitis A virus, and murine cytomegalovirus in human plasma, respectively. Laser-treated plasma showed ≥70% retention for most coagulation factors tested. Furthermore, laser treatment did not alter the structure of a model coagulation factor, fibrinogen. Ultrashort pulsed lasers are a promising new method for chemical-free, broad-spectrum pathogen reduction in human plasma.

Throughout the long history of virus-host co-evolution, viruses have developed delicate strategies to facilitate their invasion and replication of their genome, while silencing the host immune responses through various mechanisms. The systematic characterization of viral protein-host interactions would yield invaluable information in the understanding of viral invasion/evasion, diagnosis and therapeutic treatment of a viral infection, and mechanisms of host biology. With more than 2,000 viral genomes sequenced, only a small percent of them are well investigated. The access of these viral open reading frames (ORFs) in a flexible cloning format would greatly facilitate both in vitro and in vivo virus-host interaction studies. However, the overall progress of viral ORF cloning has been slow. To facilitate viral studies, we are releasing the initiation of our panviral proteome collection of 2,035 ORF clones from 830 viral genes in the Gateway® recombinational cloning system. Here, we demonstrate several uses of our viral collection including highly efficient production of viral proteins using human cell-free expression system in vitro, global identification of host targets for rubella virus using Nucleic Acid Programmable Protein Arrays (NAPPA) containing 10,000 unique human proteins, and detection of host serological responses using micro-fluidic multiplexed immunoassays. The studies presented here begin to elucidate host-viral protein interactions with our systemic utilization of viral ORFs, high-throughput cloning, and proteomic technologies. These valuable plasmid resources will be available to the research community to enable continued viral functional studies.

Background: Cancer diagnosis in both dogs and humans is complicated by the lack of a non-invasive diagnostic test. To meet this clinical need, we apply the recently developed immunosignature assay to spontaneous canine lymphoma as clinical proof-of-concept. Here we evaluate the immunosignature as a diagnostic for spontaneous canine lymphoma at both at initial diagnosis and evaluating the disease free interval following treatment.

Methods: Sera from dogs with confirmed lymphoma (B cell n = 38, T cell n = 11) and clinically normal dogs (n = 39) were analyzed. Serum antibody responses were characterized by analyzing the binding pattern, or immunosignature, of serum antibodies on a non-natural sequence peptide microarray. Peptides were selected and tested for the ability to distinguish healthy dogs from those with lymphoma and to distinguish lymphoma subtypes based on immunophenotype. The immunosignature of dogs with lymphoma were evaluated for individual signatures. Changes in the immunosignatures were evaluated following treatment and eventual relapse.

Results: Despite being a clonal disease, both an individual immunosignature and a generalized lymphoma immunosignature were observed in each dog. The general lymphoma immunosignature identified in the initial set of dogs (n = 32) was able to predict disease status in an independent set of dogs (n = 42, 97% accuracy). A separate immunosignature was able to distinguish the lymphoma based on immunophenotype (n = 25, 88% accuracy). The individual immunosignature was capable of confirming remission three months following diagnosis. Immunosignature at diagnosis was able to predict which dogs with B cell lymphoma would relapse in less than 120 days (n = 33, 97% accuracy).

Conclusion: We conclude that the immunosignature can serve as a multilevel diagnostic for canine, and potentially human, lymphoma.

Over the last two decades, our knowledge concerning intracellular events that regulate integrin’s affinity to their soluble ligands has significantly improved. However, the mechanism of adhesion-induced integrin clustering and development of focal complexes, which could further mature to form focal adhesions, still remains under-investigated. Here we present a structural model of tandem IgC2 domains of skelemin in complex with the cytoplasmic tails of integrin α[subscript IIb]β[subscript 3]. The model of tertiary assembly is generated based upon NMR data and illuminates a potential link between the essential cell adhesion receptors and myosin filaments. This connection may serve as a basis for generating the mechanical forces necessary for cell migration and remodeling.

DNA can be programmed to self-assemble into high molecular weight 3D assemblies with precise nanometer-scale structural features. Although numerous sequence design strategies exist to realize these assemblies in solution, there is currently no computational framework to predict their 3D structures on the basis of programmed underlying multi-way junction topologies constrained by DNA duplexes. Here, we introduce such an approach and apply it to assemblies designed using the canonical immobile four-way junction. The procedure is used to predict the 3D structure of high molecular weight planar and spherical ring-like origami objects, a tile-based sheet-like ribbon, and a 3D crystalline tensegrity motif, in quantitative agreement with experiments. Our framework provides a new approach to predict programmed nucleic acid 3D structure on the basis of prescribed secondary structure motifs, with possible application to the design of such assemblies for use in biomolecular and materials science.

Emerging and re-emerging infectious diseases of zoonotic origin like highly pathogenic avian influenza pose a significant threat to human and animal health due to their elevated transmissibility. Identifying the drivers of such viruses is challenging, and estimation of spatial diffusion is complicated by the fact that the variability of viral spread from locations could be caused by a complex array of unknown factors. Several techniques exist to help identify these drivers, including bioinformatics, phylogeography, and spatial epidemiology, but these methods are generally evaluated separately and do not consider the complementary nature of each other. Here, we studied an approach that integrates these techniques and identifies the most important drivers of viral spread by focusing on H5N1 influenza A virus in Egypt because of its recent emergence as an epicenter for the disease. We used a Bayesian phylogeographic generalized linear model (GLM) to reconstruct spatiotemporal patterns of viral diffusion while simultaneously assessing the impact of factors contributing to transmission. We also calculated the cross-species transmission rates among hosts in order to identify the species driving transmission. The densities of both human and avian species were supported contributors, along with latitude, longitude, elevation, and several meteorological variables. Also supported was the presence of a genetic motif found near the hemagglutinin cleavage site. Various genetic, geographic, demographic, and environmental predictors each play a role in H1N1 diffusion. Further development and expansion of phylogeographic GLMs such as this will enable health agencies to identify variables that can curb virus diffusion and reduce morbidity and mortality.

Using supported ionic-liquid membrane (SILM)-inspired methodologies, we have synthesized, characterized, and developed a humidity sensor by coating a liquid composite material onto a hygroscopic, porous substrate. Similar to pH paper, the sensor responds to the environment’s relative humidity and changes color accordingly. The humidity indicator is prepared by casting a few microliters of low-toxicity reagents on a nontoxic substrate. The sensing material is a newly synthesized liquid composite that comprises a hygroscopic medium for environmental humidity capture and a color indicator that translates the humidity level into a distinct color change. Sodium borohydride was used to form a liquid composite medium, and DenimBlu30 dye was used as a redox indicator. The liquid composite medium provides a hygroscopic response to the relative humidity, and DenimBlu30 translates the chemical changes into a visual change from yellow to blue. The borate–redox dye-based humidity sensor was prepared, and then Fourier transform infrared spectroscopy, differential scanning calorimetry, and image analysis methods were used to characterize the chemical composition, optimize synthesis, and gain insight into the sensor reactivity. Test results indicated that this new sensing material can detect relative humidity in the range of 5–100% in an irreversible manner with good reproducibility and high accuracy. The sensor is a low-cost, highly sensitive, easy-to-use humidity indicator. More importantly, it can be easily packaged with products to monitor humidity levels in pharmaceutical and food packaging.

A meta-analysis was conducted to inform the epistemology, or theory of knowledge, of contaminants of emerging concern (CECs). The CEC terminology acknowledges the existence of harmful environmental agents whose identities, occurrences, hazards, and effects are not sufficiently understood. Here, data on publishing activity were analyzed for 12 CECs, revealing a common pattern of emergence, suitable for identifying past years of peak concern and forecasting future ones: dichlorodiphenyltrichloroethane (DDT; 1972, 2008), trichloroacetic acid (TCAA; 1972, 2009), nitrosodimethylamine (1984), methyl tert-butyl ether (2001), trichloroethylene (2005), perchlorate (2006), 1,4-dioxane (2009), prions (2009), triclocarban (2010), triclosan (2012), nanomaterials (by 2016), and microplastics (2022 ± 4). CECs were found to emerge from obscurity to the height of concern in 14.1 ± 3.6 years, and subside to a new baseline level of concern in 14.5 ± 4.5 years. CECs can emerge more than once (e.g., TCAA, DDT) and the multifactorial process of emergence may be driven by inception of novel scientific methods (e.g., ion chromatography, mass spectrometry and nanometrology), scientific paradigm shifts (discovery of infectious proteins), and the development, marketing and mass consumption of novel products (antimicrobial personal care products, microplastics and nanomaterials). Publishing activity and U.S. regulatory actions were correlated for several CECs investigated.

Collective behaviors in social insect societies often emerge from simple local rules. However, little is known about how these behaviors are dynamically regulated in response to environmental changes. Here, we use a compartmental modeling approach to identify factors that allow harvester ant colonies to regulate collective foraging activity in response to their environment. We propose a set of differential equations describing the dynamics of: (1) available foragers inside the nest, (2) active foragers outside the nest, and (3) successful returning foragers, to understand how colony-specific parameters, such as baseline number of foragers, interactions among foragers, food discovery rates, successful forager return rates, and foraging duration might influence collective foraging dynamics, while maintaining functional robustness to perturbations. Our analysis indicates that the model can undergo a forward (transcritical) bifurcation or a backward bifurcation depending on colony-specific parameters. In the former case, foraging activity persists when the average number of recruits per successful returning forager is larger than one. In the latter case, the backward bifurcation creates a region of bistability in which the size and fate of foraging activity depends on the distribution of the foraging workforce among the model׳s compartments. We validate the model with experimental data from harvester ants (Pogonomyrmex barbatus) and perform sensitivity analysis. Our model provides insights on how simple, local interactions can achieve an emergent and robust regulatory system of collective foraging activity in ant colonies.