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The Arctic Ocean is more susceptible to ocean acidification than other marine environments due to its weaker buffering capacity, while its cold surface water with relatively low salinity promotes atmospheric CO2 uptake. We studied how sea-ice microbial communities in the central Arctic Ocean may be affected by changes in the carbonate system expected as a consequence of ocean acidification. In a series of four experiments during late summer 2018 aboard the icebreaker Oden, we addressed microbial growth, production of dissolved organic carbon (DOC) and extracellular polymeric substances (EPS), photosynthetic activity, and bacterial assemblage structure as sea-ice microbial communities were exposed to elevated partial pressures of CO2 (pCO(2)). We incubated intact, bottom ice-core sections and dislodged, under-ice algal aggregates (dominated by Melosira arctica) in separate experiments under approximately 400, 650, 1000, and 2000 mu atm pCO(2) for 10 d under different nutrient regimes. The results indicate that the growth of sea-ice algae and bacteria was unaffected by these higher pCO(2) levels, and concentrations of DOC and EPS were unaffected by a shifted inorganic C/N balance, resulting from the CO2 enrichment. These central Arctic sea-ice microbial communities thus appear to be largely insensitive to short-term pCO(2) perturbations. Given the natural, seasonally driven fluctuations in the carbonate system of sea ice, its resident microorganisms may be sufficiently tolerant of large variations in pCO(2) and thus less vulnerable than pelagic communities to the impacts of ocean acidification, increasing the ecological importance of sea-ice microorganisms even as the loss of Arctic sea ice continues.

A variety of ecologically important processes are driven by bacterial motility and taxis, yet these basic bacterial behaviours remain understudied in cold habitats. Here, we present a series of experiments designed to test the chemotactic ability of the model marine psychrophilic bacterium Colwellia psychrerythraea 34H, when grown at optimal temperature and salinity (8°C, 35 ppt) or its original isolation conditions (-1°C, 35 ppt), towards serine and mannose at temperatures from -8°C to 27°C (above its upper growth temperature of 18°C), and at salinities of 15, 35 and 55 ppt (at 8°C and -1°C). Results indicate that C. psychrerythraea 34H is capable of chemotaxis at all temperatures tested, with strongest chemotaxis at the temperature at which it was first grown, whether 8°C or -1°C. This model marine psychrophile also showed significant halotaxis towards 15 and 55 ppt solutions, as well as strong substrate-specific chemohalotaxis. We suggest that such patterns of taxis may enable bacteria to colonize sea ice, position themselves optimally within its extremely cold, hypersaline and temporally fluctuating microenvironments, and respond to various chemical signals therein.

Glioblastoma multiforme (GBM) is the most common and malignant form of primary brain tumors. It is highly invasive and current treatment options have not improved the survival rate over the past twenty years. Novel approaches and technologies from systems biology have the potential to identify biomarkers that could serve as new therapeutic targets for GBM. This study employed Address correspondence to these authors at the Department of Technology Leadership and Innovation, Department of Agricultural and Biological Engineering, Bindley Bioscience Center, Purdue University, 155 S. Grant Street, Young Hall 367, West Lafayette, IN 47907, USA; Tel: (765) 494-4649; kclase@purdue.edu;. Herman B Wells Center for Pediatric Research, Riley Hospital for Children at IU Health, 1044 West Walnut Street R4 302, Indianapolis, IN 46202-5525, USA; Tel: (317) 274-8891; kpollok@iu.edu. AUTHORS’ CONTRIBUTIONS Kari Clase was responsible for leading the collaboration, analyzing data and interpreting findings within the context of the biological system and establishing the data collection and sample analysis pipeline. Soo Jung Ha and Gordon M. Showalter conducted the sample preparation, mass spectrometry data collection and statistical data analysis. Jiri Adamec supervised mass spectrometry data collection. John Springer conducted statistical clustering analysis of mass spectrometry data. Shanbao Cai, Haiyan Wang, Wei M. Liu were directly responsible for intellectual input on model set up. They also set up all flank and orthotopic model, mouse monitoring, and isolation of tumor samples. Karen Pollok was responsible regulatory requirements, intellectual input, and all aspects of in vivo model set up, monitoring, and sample collection. Jenna Rickus provided intellectual input. Jann Sarkaria provided tumor cell lines and intellectual input. Aaron Cohen-Gadol provided intellectual input. CONFLICT OF INTEREST The authors confirm that there is no conflict of interest with the data presented in this article. HHS Public Access Author manuscript Anal Chem. Author manuscript; available in PMC 2016 April 29. Published in final edited form as: Anal Chem. 2007 November 15; 79(22): 8423–8430. doi:10.1021/ac071413m. A uhor M anscript

Recent advances in digital technologies, such as high-speed computers and large-format digital imagers, have led to a burgeoning interest in the science and engineering of digital holographic microscopy (DHM). Here we report on a novel off-axis DHM, based on a twin-beam optical design, which avoids the limitations of prior systems, and provides many advantages, including compactness, intrinsic stability, robustness against misalignment, ease of use, and cost. These advantages are traded for a physically constrained sample volume, as well as a fixed fringe spacing. The first trade is not overly restrictive for most applications, and the latter provides for a pre-set assembly alignment that optimizes the spatial frequency sampling. Moreover, our new design supports use in both routine laboratory settings as well as extreme environments without any sacrifice in performance, enabling ready observation of microbial species in the field. The instrument design is presented in detail here, along with a demonstration of bacterial video imaging at sub-micrometer resolution at temperatures down to –15 °C.

Glioblastoma (GBM) is the most common and malignant form of primary brain tumor. Average survival rate of GBM is 12-15 months from diagnosis. Due to its highly invasive nature, current treatment options have not been able to improve the survival rate in past 20 years. In order to discover GBM therapeutic targets, omics technologies have been widely used in order to identify potential biomarkers. Identification of cancer biomarkers for diagnosis and prognosis continues to evolve as clinical specimen pipelines and technologies are optimized. This research study focused on investigating proteins, metabolites and lipids biomarkers and patterns of human GBM xenografts employing mass spectrometry. Human tumor cell lines GBM 10 and GBM 43 were injected in the right cerebral hemisphere and flank sites in NOD/SCID mice (n = 10 mice per group). After harvesting brain and flank tumors and control brain from mouse models, protein, metabolites, and lipids of tumor samples were collected through one simple extraction procedure, which may solve sample preparation difficulties in omics studies, developed by Dr. Jiri Adamec. These samples were analyzed by reverse phase high performance liquid chromatography - Fourier transform ion cyclotron resonance mass spectrometry (LC-FTMS). FTMS analyzers have the highest resolving power of all MS instruments, which is ideal for complex mixtures such as GBM tissue. Spectra obtained from the FTMS analysis were analyzed using Student t-tests to detect significant differences in tissue profiles at a level of p = 0.05. Compounds below this threshold were identified through a database using the m/z ratio. Lipidomic analysis indicated the possible up and down-regulation of several lipids classes in GBM tissue connected to metabolic pathways, tumor proliferation and immunodepression, such as glycerophospholipids, both up- and down-regulated (e.g. PC38:4 or PG 35:2, respectively), and down-regulated glycosphingolipids (Galβ1-3GlcNAcβ1-3Galβ1-4Glc-Cer, Galβ1-4GlcNAcβ1-3Galβ1-4Glc-Cer), and triglycerides (TG 55:9, 53:4,52:8). We expect that integrated studies of proteomics, metabolomics, and lipidomics increase the confidence of identification of potential biomarkers. Accompanying these studies is a collaborative effort to improve the effectiveness and efficiency of computational pipelines that are imperative to the analytics, visualization, identification, and interpretation of the omics data. Only by carefully integrating the computational pipelines can we successfully perform the types of integrative studies needed to advance the identification of cancer biomarkers for diagnosis and prognosis, and our integrative studies serve as a case study for our pipeline advancement efforts. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):B37. Citation Format: Soo Jung Ha, Gordon Showalter, Jenna Rickus, Shanbao Cai, Haiyan Wang, Wei Michael Liu, Jann N. Sarkaria, John Springer, Jiri Adamec, Karen E. Pollok, Kari L. Clase. Proteomic and metabolomic analyses of glioblastoma using mass spectrometry. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr B37.