Addressing accuracy and precision issues in iTRAQ quantitation

iTRAQ (isobaric tags for relative or absolute quantitation) is a mass spectrometry technology that allows quantitative comparison of protein abundance by measuring peak intensities of reporter ions released from iTRAQ-tagged peptides by fragmentation during MS/MS. However, current data analysis techniques for iTRAQ struggle to report reliable relative protein abundance estimates and suffer with problems of precision and accuracy. The precision of the data is affected by variance heterogeneity: low signal data have higher relative variability; however, low abundance peptides dominate data sets. Accuracy is compromised as ratios are compressed toward 1, leading to underestimation of the ratio. This study investigated both issues and proposed a methodology that combines the peptide measurements to give a robust protein estimate even when the data for the protein are sparse or at low intensity. Our data indicated that ratio compression arises from contamination during precursor ion selection, which occurs at a consistent proportion within an experiment and thus results in a linear relationship between expected and observed ratios. We proposed that a correction factor can be calculated from spiked proteins at known ratios. Then we demonstrated that variance heterogeneity is present in iTRAQ data sets irrespective of the analytical packages, LC-MS/MS instrumentation, and iTRAQ labeling kit (4-plex or 8-plex) used. We proposed using an additive-multiplicative error model for peak intensities in MS/MS quantitation and demonstrated that a variance-stabilizing normalization is able to address the error structure and stabilize the variance across the entire intensity range. The resulting uniform variance structure simplifies the downstream analysis. Heterogeneity of variance consistent with an additive-multiplicative model has been reported in other MS-based quantitation including fields outside of proteomics; consequently the variance-stabilizing normalization methodology has the potential to increase the capabilities of MS in quantitation across diverse areas of biology and chemistry.

A methodology for effective implementation of lean strategies and its performance evaluation in manufacturing organizations

Purpose – The purpose of this paper is to develop an effective methodology for implementing lean manufacturing strategies and a leanness evaluation metric using continuous performance measurement (CPM). Design/methodology/approach – Based on five lean principles, a systematic lean implementation methodology for manufacturing organizations has been proposed. A simplified leanness evaluation metric consisting of both efficiency and effectiveness attributes of manufacturing performance has been developed for continuous evaluation of lean implementation. A case study to validate the proposed methodology has been conducted and proposed CPM metric has been used to assess the manufacturing leanness. Findings – Proposed methodology is able to systematically identify manufacturing wastes, select appropriate lean tools, identify relevant performance indicators, achieve significant performance improvement and establish lean culture in the organization. Continuous performance measurement matrices in terms of efficiency and effectiveness are proved to be appropriate methods for continuous evaluation of lean performance. Research limitations/implications – Effectiveness of the method developed has been demonstrated by applying it in a real life assembly process. However, more tests/applications will be necessary to generalize the findings. Practical implications – Results show that applying the methods developed, managers can successfully identify and remove manufacturing wastes from their production processes. By improving process efficiency, they can optimize their resource allocations. Manufacturers now have a validated step by step methodology for successfully implementing lean strategies. Originality/value – According to the authors’ best knowledge, this is the first known study that proposed a systematic lean implementation methodology based on lean principles and continuous improvement techniques. Evaluation of performance improvement by lean strategies is a critical issue. This study develops a simplified leanness evaluation metric considering both efficiency and effectiveness attributes and integrates it with the lean implementation methodology.

Local stress-strain distribution and load transfer across cartilage matrix at micro-scale using combined microscopy-based finite element method

Articular cartilage is the load-bearing tissue that consists of proteoglycan macromolecules entrapped between collagen fibrils in a three-dimensional architecture. To date, the drudgery of searching for mathematical models to represent the biomechanics of such a system continues without providing a fitting description of its functional response to load at micro-scale level. We believe that the major complication arose when cartilage was first envisaged as a multiphasic model with distinguishable components and that quantifying those and searching for the laws that govern their interaction is inadequate. To the thesis of this paper, cartilage as a bulk is as much continuum as is the response of its components to the external stimuli. For this reason, we framed the fundamental question as to what would be the mechano-structural functionality of such a system in the total absence of one of its key constituents-proteoglycans. To answer this, hydrated normal and proteoglycan depleted samples were tested under confined compression while finite element models were reproduced, for the first time, based on the structural microarchitecture of the cross-sectional profile of the matrices. These micro-porous in silico models served as virtual transducers to produce an internal noninvasive probing mechanism beyond experimental capabilities to render the matrices micromechanics and several others properties like permeability, orientation etc. The results demonstrated that load transfer was closely related to the microarchitecture of the hyperelastic models that represent solid skeleton stress and fluid response based on the state of the collagen network with and without the swollen proteoglycans. In other words, the stress gradient during deformation was a function of the structural pattern of the network and acted in concert with the position-dependent compositional state of the matrix. This reveals that the interaction between indistinguishable components in real cartilage is superimposed by its microarchitectural state which directly influences macromechanical behavior.

Delineating breast cancer cell interactions with engineered bone microenvironments

The mechanisms leading to colonization of metastatic breast cancer cells (BCa) in the skeleton are still not fully understood. Here, we demonstrate that mineralized extracellular matrices secreted by primary human osteoblasts (hOBM) modulate cellular processes associated with BCa colonization of bone. A panel of four BCa cell lines of different bone-metastatic potential (T47D, SUM1315, MDA-MB-231, and the bone-seeking subline MDA-MB-231BO) was cultured on hOBM. After 3 days, the metastatic BCa cells had undergone morphological changes on hOBM and were aligned along the hOBM's collagen type I fibrils that were decorated with bone-specific proteins. In contrast, nonmetastatic BCa cells showed a random orientation on hOBM. Atomic force microscopy-based single-cell force spectroscopy revealed that the metastatic cell lines adhered more strongly to hOBM compared with nonmetastatic cells. Function-blocking experiments indicated that β1-integrins mediated cell adhesion to hOBM. In addition, metastatic BCa cells migrated directionally and invaded hOBM, which was accompanied by enhanced MMP-2 and -9 secretion. Furthermore, we observed gene expression changes associated with osteomimickry in BCa cultured on hOBM. As such, osteopontin mRNA levels were significantly increased in SUM1315 and MDA-MB-231BO cells in a β1-integrin-dependent manner after growing for 3 days on hOBM compared with tissue culture plastic. In conclusion, our results show that extracellular matrices derived from human osteoblasts represent a powerful experimental platform to dissect mechanisms underlying critical steps in the development of bone metastases.

A bioengineered 3D ovarian cancer model for the assessment of peptidase-mediated enhancement of spheroid growth and intraperitoneal spread

Cancer-associated proteases promote peritoneal dissemination and chemoresistance in malignant progression. In this study, kallikrein-related peptidases 4, 5, 6, and 7 (KLK4-7)-cotransfected OV-MZ-6 ovarian cancer cells were embedded in a bioengineered three-dimensional (3D) microenvironment that contains RGD motifs for integrin engagement to analyze their spheroid growth and survival after chemotreatment. KLK4-7-cotransfected cells formed larger spheroids and proliferated more than controls in 3D, particularly within RGD-functionalized matrices, which was reduced upon integrin inhibition. In contrast, KLK4-7-expressing cell monolayers proliferated less than controls, emphasizing the relevance of the 3D microenvironment and integrin engagement. In a spheroid-based animal model, KLK4-7-overexpression induced tumor growth after 4 weeks and intraperitoneal spread after 8 weeks. Upon paclitaxel administration, KLK4-7-expressing tumors declined in size by 91% (controls: 87%) and showed 90% less metastatic outgrowth (controls: 33%, P<0.001). KLK4-7-expressing spheroids showed 53% survival upon paclitaxel treatment (controls: 51%), accompanied by enhanced chemoresistance-related factors, and their survival was further reduced by combination treatment of paclitaxel with KLK4/5/7 (22%, P=0.007) or MAPK (6%, P=0.006) inhibition. The concomitant presence of KLK4-7 in ovarian cancer cells together with integrin activation drives spheroid formation and proliferation. Combinatorial approaches of paclitaxel and KLK/MAPK inhibition may be more efficient for late-stage disease than chemotherapeutics alone as these inhibitory regimens reduced cancer spheroid growth to a greater extent than paclitaxel alone.