Biology subjects

Ram, S.

Publications and source records attributed to Ram, S..

3 recordsLinked to original sources

bioRxiv2018

Information theoretic analysis of hyperspectralimaging systems with applications to fluorescencemicroscopy

We present a general stochastic model for hyperspectral imaging data and derive analytical expressions for the Fisher information matrix for the underlying spectral unmixing problem. We investigate the linear mixing model as a special case and define a linear unmixing performance bound by using the Cramer-Rao inequality. As an application, we consider fluorescence imaging and show how the performance bound provides a spectral resolution limit that predicts how accurately a pair of spectrally similar fluorescent labels can be spectrally unmixed. We also report a novel result that shows how the spectral resolution limit can be overcome by exploiting the phenomenon of anti-Stokes shift fluorescence. In addition, we investigate how photon statistics, channel addition and channel splitting affect the performance bound. Finally by using the performance bound as a benchmark, we compare the performance of the least squares and the maximum likelihood estimators for spectral unmixing. For the imaging conditions tested here, our analysis shows that both estimators are unbiased and that the standard deviation of the maximum likelihood estimator is consistently closer to the performance bound than that of the least squares estimator. The results presented here are based on broad assumptions regarding the underlying data model and are applicable to hyperspectral data acquired with point detectors, sCMOS, CCD and EMCCD imaging detectors.\n\nEDICS: ELI-COL, COI-MCI.

bioengineering↗

bioRxiv2018

A novel sialylation site on Neisseria gonorrhoeae lipooligosaccharide links heptose II lactose expression with pathogenicity

Sialylation of lacto-W-neotetraose (LNnT) extending from heptose I (HepI) of gonococcal lipooligosaccharide (LOS) contributes to pathogenesis. Previously, gonococcal LOS sialyltransterase (Lst) was shown to sialylate LOS in Triton X-100 extracts of strain 15253, which expresses lactose from both HepI and HepII, the minimal structure required for mAb 2C7 binding. Ongoing work has shown that growth of 15253 in cytidine monophospho-W-acetylneuraminic acid (CMP-Neu5Ac)-containing media enables binding to CD33/Siglec-3, a cell surface receptor that binds sialic acid, suggesting that lactose termini on LOS of intact gonococci can be sialylated. Neu5Ac was detected on LOSs of strains 15253 and a MS11 mutant with only lactose from HepI and HepII by mass spectrometry; deleting HepII lactose rendered Neu5Ac undetectable. Resistance of HepII lactose Neu5Ac to desialylation by 2-3-specific neuraminidase suggested an 2-6-linkage. Although not associated with increased factor H binding, HepII lactose sialylation inhibited complement C3 deposition on gonococci. 15253 mutants that lacked Lst or HepII lactose were significantly attenuated in mice, confirming the importance of HepII Neu5Ac in virulence. All 75 minimally passaged clinical isolates from Nanjing, China, expressed HepII lactose, evidenced by reactivity with mAb 2C7; mAb 2C7 was bactericidal against the first 62 (of 75) isolates that had been collected sequentially and were sialylated before testing. mAb 2C7 effectively attenuated 15253 vaginal colonization in mice. In conclusion, this novel sialylation site could explain the ubiquity of gonococcal HepII lactose in vivo. Our findings reiterate the candidacy of the 2C7 epitope as a vaccine antigen and mAb 2C7 as an immunotherapeutic antibody.

microbiology↗

bioRxiv2016

Intensity-based axial localization approaches for multifocal plane microscopy

Multifocal plane microscopy (MUM) can be used to visualize biological samples in three dimensions over large axial depths and provides for the high axial localization accuracy that is needed in applications such as the three-dimensional tracking of single particles and superresolution microscopy. This report analyzes the performance of intensity-based axial localization approaches as applied to MUM data using Fisher information calculations. In addition, a new non-parametric intensity-based axial location estimation method, Multi-Intensity Lookup Algorithm (MILA), is introduced that, unlike typical intensity-based methods that make use of a single intensity value per data image, utilizes multiple intensity values per data image in determining the axial location of a point source. MILA is shown to be robust against potential bias induced by differences in the sub-pixel location of the imaged point source. The method's effectiveness on experimental data is also evaluated.

biophysics↗