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This study explores the capabilities of the Coherent X-ray Imaging Instrument at the Linac Coherent Light Source to image small biological samples. The weak signal from small samples puts a significant demand on the experiment. Aerosolized Omono River virus particles of ∼40 nm in diameter were injected into the submicrometre X-ray

This study explores the capabilities of the Coherent X-ray Imaging Instrument at the Linac Coherent Light Source to image small biological samples. The weak signal from small samples puts a significant demand on the experiment. Aerosolized Omono River virus particles of ∼40 nm in diameter were injected into the submicrometre X-ray focus at a reduced pressure. Diffraction patterns were recorded on two area detectors. The statistical nature of the measurements from many individual particles provided information about the intensity profile of the X-ray beam, phase variations in the wavefront and the size distribution of the injected particles. The results point to a wider than expected size distribution (from ∼35 to ∼300 nm in diameter). This is likely to be owing to nonvolatile contaminants from larger droplets during aerosolization and droplet evaporation. The results suggest that the concentration of nonvolatile contaminants and the ratio between the volumes of the initial droplet and the sample particles is critical in such studies. The maximum beam intensity in the focus was found to be 1.9 × 1012 photons per µm2 per pulse. The full-width of the focus at half-maximum was estimated to be 500 nm (assuming 20% beamline transmission), and this width is larger than expected. Under these conditions, the diffraction signal from a sample-sized particle remained above the average background to a resolution of 4.25 nm. The results suggest that reducing the size of the initial droplets during aerosolization is necessary to bring small particles into the scope of detailed structural studies with X-ray lasers.

ContributorsDaurer, Benedikt J. (Author) / Okamoto, Kenta (Author) / Bielecki, Johan (Author) / Maia, Filipe R. N. C. (Author) / Muhlig, Kerstin (Author) / Seibert, M. Marvin (Author) / Hantke, Max F. (Author) / Nettelblad, Carl (Author) / Benner, W. Henry (Author) / Svenda, Martin (Author) / Timneanu, Nicusor (Author) / Ekeberg, Tomas (Author) / Loh, N. Duane (Author) / Pietrini, Alberto (Author) / Zani, Alessandro (Author) / Rath, Asawari D. (Author) / Westphal, Daniel (Author) / Kirian, Richard (Author) / Awel, Salah (Author) / Wiedorn, Max O. (Author) / van der Schot, Gijs (Author) / Carlsson, Gunilla H. (Author) / Hasse, Dirk (Author) / Sellberg, Jonas A. (Author) / Barty, Anton (Author) / Andreasson, Jakob (Author) / Boutet, Sebastien (Author) / Williams, Garth (Author) / Koglin, Jason (Author) / Andersson, Inger (Author) / Hajdu, Janos (Author) / Larsson, Daniel S. D. (Author) / College of Liberal Arts and Sciences (Contributor)
Created2017-04-07
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Description

Infection after renal transplantation remains a major cause of morbidity and death, especially infection from the extensively drug-resistant bacteria, A. baumannii. A total of fourteen A. baumannii isolates were isolated from the donors’ preserved fluid from DCD (donation after cardiac death) renal transplantation and four isolates in the recipients’ draining

Infection after renal transplantation remains a major cause of morbidity and death, especially infection from the extensively drug-resistant bacteria, A. baumannii. A total of fourteen A. baumannii isolates were isolated from the donors’ preserved fluid from DCD (donation after cardiac death) renal transplantation and four isolates in the recipients’ draining liquid at the Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, from March 2013 to November 2014. An outbreak of A. baumannii emerging after DCD renal transplantation was tracked to understand the transmission of the pathogen. PFGE displayed similar DNA patterns between isolates from the same hospital. Antimicrobial susceptibility tests against thirteen antimicrobial agents were determined using the K-B diffusion method and eTest. Whole-genome sequencing was applied to investigate the genetic relationship of the isolates. With the clinical data and research results, we concluded that the A. baumannii isolates 3R1 and 3R2 was probably transmitted from the donor who acquired the bacteria during his stay in the ICU, while isolate 4R1 was transmitted from 3R1 and 3R2 via medical manipulation. This study demonstrated the value of integration of clinical profiles with molecular methods in outbreak investigation and their importance in controlling infection and preventing serious complications after DCD transplantation.

ContributorsJiang, Hong (Author) / Cao, Luxi (Author) / Qu, Lihui (Author) / Qu, Tingting (Author) / Liu, Guangjun (Author) / Wang, Rending (Author) / Li, Bingjue (Author) / Wang, Yuchen (Author) / Ying, Chaoqun (Author) / Chen, Miao (Author) / Lu, Yingying (Author) / Feng, Shi (Author) / Xiao, Yonghong (Author) / Wang, Junwen (Author) / Wu, Jianyong (Author) / Chen, Jianghua (Author) / College of Health Solutions (Contributor)
Created2017-05-16
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Description

Intercellular interactions play a central role at the tissue and whole organism level modulating key cellular functions in normal and disease states. Studies of cell-cell communications are challenging due to ensemble averaging effects brought about by intrinsic heterogeneity in cellular function which requires such studies to be conducted with small

Intercellular interactions play a central role at the tissue and whole organism level modulating key cellular functions in normal and disease states. Studies of cell-cell communications are challenging due to ensemble averaging effects brought about by intrinsic heterogeneity in cellular function which requires such studies to be conducted with small populations of cells. Most of the current methods for producing and studying such small cell populations are complex to implement and require skilled personnel limiting their widespread utility in biomedical research labs. We present a simple and rapid method to produce small populations with varying size of epithelial cells (10–50 cells/population) with high-throughput (~1 population/second) on flat surfaces via patterning of extracellular matrix (ECM) proteins and random seeding of cells. We demonstrate that despite inherent limitations of non-contact, drop-on-demand piezoelectric inkjet printing for protein patterning, varying mixtures of ECM proteins can be deposited with high reproducibility and level of control on glass substrates using a set of dynamically adjustable optimized deposition parameters. We demonstrate high consistency for the number of cells per population (~1 cell standard error of mean), the population’s size (~0.2 coefficient of variation) and shape, as well as accurate spatial placement of and distance between colonies of a panel of metaplastic and dysplastic esophageal epithelial cells with differing adhesion and motility characteristics. The number of cells per colony, colony size and shape can be varied by dynamically varying the amount of ECM proteins deposited per spatial location and the number of spatial locations on the substrate. The method is applicable to a broad range of biological and biomedical studies including cell-cell communications, cellular microenvironment, migration, and stimulus response.

ContributorsLee, Kristen (Author) / Kelbauskas, Laimonas (Author) / Brunner, Alan (Author) / Meldrum, Deirdre (Author) / Biodesign Institute (Contributor)
Created2017-04-26
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Description

Whole genome sequencing (WGS) is a promising strategy to unravel variants or genes responsible for human diseases and traits. However, there is a lack of robust platforms for a comprehensive downstream analysis. In the present study, we first proposed three novel algorithms, sequence gap-filled gene feature annotation, bit-block encoded genotypes

Whole genome sequencing (WGS) is a promising strategy to unravel variants or genes responsible for human diseases and traits. However, there is a lack of robust platforms for a comprehensive downstream analysis. In the present study, we first proposed three novel algorithms, sequence gap-filled gene feature annotation, bit-block encoded genotypes and sectional fast access to text lines to address three fundamental problems. The three algorithms then formed the infrastructure of a robust parallel computing framework, KGGSeq, for integrating downstream analysis functions for whole genome sequencing data. KGGSeq has been equipped with a comprehensive set of analysis functions for quality control, filtration, annotation, pathogenic prediction and statistical tests. In the tests with whole genome sequencing data from 1000 Genomes Project, KGGSeq annotated several thousand more reliable non-synonymous variants than other widely used tools (e.g. ANNOVAR and SNPEff). It took only around half an hour on a small server with 10 CPUs to access genotypes of ∼60 million variants of 2504 subjects, while a popular alternative tool required around one day. KGGSeq's bit-block genotype format used 1.5% or less space to flexibly represent phased or unphased genotypes with multiple alleles and achieved a speed of over 1000 times faster to calculate genotypic correlation.

ContributorsLi, Miaoxin (Author) / Li, Jiang (Author) / Li, Mulin Jun (Author) / Pan, Zhicheng (Author) / Hsu, Jacob Shujui (Author) / Liu, Dajiang J. (Author) / Zhan, Xiaowei (Author) / Wang, Junwen (Author) / Song, Youqiang (Author) / Sham, Pak Chung (Author) / College of Health Solutions (Contributor)
Created2017-01-23
Description

The glucose metabolism level reflects cell proliferative status. A polymeric glucose ratiometric sensor comprising poly(N-(2-hydroxypropyl)methacrylamide) (PHPMA) and poly[2-(methacryloyloxy)ethyl]trimethylammonium chloride (PMAETMA) was synthesized. Cellular internalization and glucose response of the polymer within HeLa cells were investigated.

ContributorsZhang, Liqiang (Author) / Su, Fengyu (Author) / Buizer, Sean (Author) / Kong, Xiangxing (Author) / Lee, Fred (Author) / Day, Kevin (Author) / Tian, Yanqing (Author) / Meldrum, Deirdre (Author) / Biodesign Institute (Contributor)
Created2014-05-07
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Description

Precise spatial positioning and isolation of mammalian cells is a critical component of many single cell experimental methods and biological engineering applications. Although a variety of cell patterning methods have been demonstrated, many of these methods subject cells to high stress environments, discriminate against certain phenotypes, or are a challenge

Precise spatial positioning and isolation of mammalian cells is a critical component of many single cell experimental methods and biological engineering applications. Although a variety of cell patterning methods have been demonstrated, many of these methods subject cells to high stress environments, discriminate against certain phenotypes, or are a challenge to implement. Here, we demonstrate a rapid, simple, indiscriminate, and minimally perturbing cell patterning method using a laser fabricated polymer stencil. The stencil fabrication process requires no stencil-substrate alignment, and is readily adaptable to various substrate geometries and experiments.

ContributorsMessner, Jacob J. (Author) / Glenn, Honor (Author) / Meldrum, Deirdre (Author) / Biodesign Institute (Contributor)
Created2017-12-19
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Description

Modeling of transcriptional regulatory networks (TRNs) has been increasingly used to dissect the nature of gene regulation. Inference of regulatory relationships among transcription factors (TFs) and genes, especially among multiple TFs, is still challenging. In this study, we introduced an integrative method, LogicTRN, to decode TF–TF interactions that form TF

Modeling of transcriptional regulatory networks (TRNs) has been increasingly used to dissect the nature of gene regulation. Inference of regulatory relationships among transcription factors (TFs) and genes, especially among multiple TFs, is still challenging. In this study, we introduced an integrative method, LogicTRN, to decode TF–TF interactions that form TF logics in regulating target genes. By combining cis-regulatory logics and transcriptional kinetics into one single model framework, LogicTRN can naturally integrate dynamic gene expression data and TF-DNA-binding signals in order to identify the TF logics and to reconstruct the underlying TRNs. We evaluated the newly developed methodology using simulation, comparison and application studies, and the results not only show their consistence with existing knowledge, but also demonstrate its ability to accurately reconstruct TRNs in biological complex systems.

ContributorsYan, Bin (Author) / Guan, Daogang (Author) / Wang, Chao (Author) / Wang, Junwen (Author) / He, Bing (Author) / Qin, Jing (Author) / Boheler, Kenneth R. (Author) / Lu, Aiping (Author) / Zhang, Ge (Author) / Zhu, Hailong (Author) / College of Health Solutions (Contributor)
Created2017-10-19
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Description

Quantitative three-dimensional (3D) computed tomography (CT) imaging of living single cells enables orientation-independent morphometric analysis of the intricacies of cellular physiology. Since its invention, x-ray CT has become indispensable in the clinic for diagnostic and prognostic purposes due to its quantitative absorption-based imaging in true 3D that allows objects of

Quantitative three-dimensional (3D) computed tomography (CT) imaging of living single cells enables orientation-independent morphometric analysis of the intricacies of cellular physiology. Since its invention, x-ray CT has become indispensable in the clinic for diagnostic and prognostic purposes due to its quantitative absorption-based imaging in true 3D that allows objects of interest to be viewed and measured from any orientation. However, x-ray CT has not been useful at the level of single cells because there is insufficient contrast to form an image. Recently, optical CT has been developed successfully for fixed cells, but this technology called Cell-CT is incompatible with live-cell imaging due to the use of stains, such as hematoxylin, that are not compatible with cell viability. We present a novel development of optical CT for quantitative, multispectral functional 4D (three spatial + one spectral dimension) imaging of living single cells. The method applied to immune system cells offers truly isotropic 3D spatial resolution and enables time-resolved imaging studies of cells suspended in aqueous medium. Using live-cell optical CT, we found a heterogeneous response to mitochondrial fission inhibition in mouse macrophages and differential basal remodeling of small (0.1 to 1 fl) and large (1 to 20 fl) nuclear and mitochondrial structures on a 20- to 30-s time scale in human myelogenous leukemia cells. Because of its robust 3D measurement capabilities, live-cell optical CT represents a powerful new tool in the biomedical research field.

ContributorsKelbauskas, Laimonas (Author) / Shetty, Rishabh Manoj (Author) / Cao, Bin (Author) / Wang, Kuo-Chen (Author) / Smith, Dean (Author) / Wang, Hong (Author) / Chao, Shi-Hui (Author) / Gangaraju, Sandhya (Author) / Ashcroft, Brian (Author) / Kritzer, Margaret (Author) / Glenn, Honor (Author) / Johnson, Roger (Author) / Meldrum, Deirdre (Author) / Biodesign Institute (Contributor)
Created2017-12-06
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Description

Previous proof-of-concept measurements on single-layer two-dimensional membrane-protein crystals performed at X-ray free-electron lasers (FELs) have demonstrated that the collection of meaningful diffraction patterns, which is not possible at synchrotrons because of radiation-damage issues, is feasible. Here, the results obtained from the analysis of a thousand single-shot, room-temperature X-ray FEL diffraction

Previous proof-of-concept measurements on single-layer two-dimensional membrane-protein crystals performed at X-ray free-electron lasers (FELs) have demonstrated that the collection of meaningful diffraction patterns, which is not possible at synchrotrons because of radiation-damage issues, is feasible. Here, the results obtained from the analysis of a thousand single-shot, room-temperature X-ray FEL diffraction images from two-dimensional crystals of a bacteriorhodopsin mutant are reported in detail. The high redundancy in the measurements boosts the intensity signal-to-noise ratio, so that the values of the diffracted intensities can be reliably determined down to the detector-edge resolution of 4 Å. The results show that two-dimensional serial crystallography at X-ray FELs is a suitable method to study membrane proteins to near-atomic length scales at ambient temperature. The method presented here can be extended to pump–probe studies of optically triggered structural changes on submillisecond timescales in two-dimensional crystals, which allow functionally relevant large-scale motions that may be quenched in three-dimensional crystals.

ContributorsCasadei, Cecilia M. (Author) / Tsai, Ching-Ju (Author) / Barty, Anton (Author) / Hunter, Mark S. (Author) / Zatsepin, Nadia (Author) / Padeste, Celestino (Author) / Capitani, Guido (Author) / Benner, W. Henry (Author) / Boutet, Sebastien (Author) / Hau-Riege, Stefan P. (Author) / Kupitz, Christopher (Author) / Messerschmidt, Marc (Author) / Ogren, John I. (Author) / Pardini, Tom (Author) / Rothschild, Kenneth J. (Author) / Sala, Leonardo (Author) / Segelke, Brent (Author) / Williams, Garth J. (Author) / Evans, James E. (Author) / Li, Xiao-Dan (Author) / Coleman, Matthew (Author) / Pedrini, Bill (Author) / Frank, Matthias (Author) / College of Liberal Arts and Sciences (Contributor)
Created2018-01
Description

Linnorm is a novel normalization and transformation method for the analysis of single cell RNA sequencing (scRNA-seq) data. Linnorm is developed to remove technical noises and simultaneously preserve biological variations in scRNA-seq data, such that existing statistical methods can be improved. Using real scRNA-seq data, we compared Linnorm with existing

Linnorm is a novel normalization and transformation method for the analysis of single cell RNA sequencing (scRNA-seq) data. Linnorm is developed to remove technical noises and simultaneously preserve biological variations in scRNA-seq data, such that existing statistical methods can be improved. Using real scRNA-seq data, we compared Linnorm with existing normalization methods, including NODES, SAMstrt, SCnorm, scran, DESeq and TMM. Linnorm shows advantages in speed, technical noise removal and preservation of cell heterogeneity, which can improve existing methods in the discovery of novel subtypes, pseudo-temporal ordering of cells, clustering analysis, etc. Linnorm also performs better than existing DEG analysis methods, including BASiCS, NODES, SAMstrt, Seurat and DESeq2, in false positive rate control and accuracy.

ContributorsYip, Shun H. (Author) / Wang, Panwen (Author) / Kocher, Jean-Pierre A. (Author) / Sham, Pak Chung (Author) / Wang, Junwen (Author) / College of Health Solutions (Contributor)
Created2017-09-18