Memory effects of prior subculture may impact the quality of multiomic perturbation profiles.

Mass spectrometry-based omics technologies are increasingly used in perturbation studies to map drug effects to biological pathways by identifying significant molecular events. Significance is influenced by fold change and variation of each molecular parameter, but also by multiple testing corrections. While the fold change is largely determined by the biological system, the variation is determined by experimental workflows. Here, it is shown that memory effects of prior subculture can influence the variation of perturbation profiles using the two colon carcinoma cell lines SW480 and HCT116. These memory effects are largely driven by differences in growth states that persist into the perturbation experiment. In SW480 cells, memory effects combined with moderate treatment effects amplify the variation in multiple omics levels, including eicosadomics, proteomics, and phosphoproteomics. With stronger treatment effects, the memory effect was less pronounced, as demonstrated in HCT116 cells. Subculture homogeneity was controlled by real-time monitoring of cell growth. Controlled homogeneous subculture resulted in a perturbation network of 321 causal conjectures based on combined proteomic and phosphoproteomic data, compared to only 58 causal conjectures without controlling subculture homogeneity in SW480 cells. Some cellular responses and regulatory events were identified that extend the mode of action of arsenic trioxide (ATO) only when accounting for these memory effects. Controlled prior subculture led to the finding of a synergistic combination treatment of ATO with the thioredoxin reductase 1 inhibitor auranofin, which may prove useful in the management of NRF2-mediated resistance mechanisms.

Proteomic identification of a marker signature for MAPKi resistance in melanoma.

MAPK inhibitors (MAPKi) show outstanding clinical response rates in melanoma patients harbouring BRAF mutations, but resistance is common. The ability of melanoma cells to switch from melanocytic to mesenchymal phenotypes appears to be associated with therapeutic resistance. High-throughput, subcellular proteome analyses and RNAseq on two panels of primary melanoma cells that were either sensitive or resistant to MAPKi revealed that only 15 proteins were sufficient to distinguish between these phenotypes. The two proteins with the highest discriminatory power were PTRF and IGFBP7, which were both highly upregulated in the mesenchymal-resistant cells. Proteomic analysis of CRISPR/Cas-derived PTRF knockouts revealed targets involved in lysosomal activation, endocytosis, pH regulation, EMT, TGFß signalling and cell migration and adhesion, as well as a significantly reduced invasive index and ability to form spheres in 3D culture. Overexpression of PTRF led to MAPKi resistance, increased cell adhesion and sphere formation. In addition, immunohistochemistry of patient samples showed that PTRF expression levels were a significant biomarker of poor progression-free survival, and IGFBP7 levels in patient sera were shown to be higher after relapse.

Interference Disturbance Analysis Enables Single-Cell Level Growth and Mobility Characterization for Rapid Antimicrobial Susceptibility Testing.

To support the emerging battle against antimicrobial resistance (AMR), detection methods that allow fast and accurate antimicrobial susceptibility testing (AST) are urgently needed. The early identification and application of an appropriate antibiotic treatment leads to lower mortality rates and substantial cost savings and prevents the development of resistant pathogens. In this work, we present a diffraction-based method, which is capable of quantitative bacterial growth, mobility, and susceptibility measurements. The method is based on the temporal analysis of the intensity of a light diffraction peak, which arises due to interference at a periodic pattern of gold nanostructures. The presence of bacteria disturbs the constructive interference, leading to an intensity decrease and thus allows the monitoring of bacterial growth in very low volumes. We demonstrate the direct correlation of the decrease in diffraction peak intensity with bacterial cell number starting from single cells and show the capability for rapid high-throughput AST measurements by determining the minimum inhibitory concentration for three different antimicrobials in less than 2-3 h as well as the susceptibility in less than 30-40 min. Furthermore, bacterial mobility is obtained from short-term fluctuations of the diffraction peak intensity and is shown to decrease by a factor of 3 during bacterial attachment to a surface. This multiparameter detection method allows for rapid AST of planktonic and of biofilm-forming bacterial strains in low volumes and in real-time without the need of high initial cell numbers.

Single-Cell Optical Distortion Correction and Label-Free 3D Cell Shape Reconstruction on Lattices of Nanostructures.

Imaging techniques can be compromised by aberrations. Especially when imaging through biological specimens, sample-induced distortions can limit localization accuracy. In particular, this phenomenon affects localization microscopy, traction force measurements, and single-particle tracking, which offer high-resolution insights into biological tissue. Here we present a method for quantifying and correcting the optical distortions induced by single, adherent, living cells. The technique uses periodically patterned gold nanostructures as a reference framework to quantify optically induced displacements with micrometer-scale sampling density and an accuracy of a few nanometers. The 3D cell shape and a simplified geometrical optics approach are then utilized to remap the microscope image. Our experiments reveal displacements of up to several hundred nanometers, and in corrected images these distortions are reduced by a factor of 3. Conversely, the relationship between cell shape and distortion provides a novel method of 3D cell shape reconstruction from a single image, enabling label-free 3D cell analysis.

Observing polarization patterns in the collective motion of nanomechanical arrays.

In recent years, nanomechanics has evolved into a mature field, and it has now reached a stage which enables the fabrication and study of ever more elaborate devices. This has led to the emergence of arrays of coupled nanomechanical resonators as a promising field of research serving as model systems to study collective dynamical phenomena such as synchronization or topological transport. From a general point of view, the arrays investigated so far can be effectively treated as scalar fields on a lattice. Moving to a scenario where the vector character of the fields becomes important would unlock a whole host of conceptually interesting additional phenomena, including the physics of polarization patterns in wave fields and their associated topology. Here we introduce a new platform, a two-dimensional array of coupled nanomechanical pillar resonators, whose orthogonal vibration directions encode a mechanical polarization degree of freedom. We demonstrate direct optical imaging of the collective dynamics, enabling us to analyze the emerging polarization patterns, follow their evolution with drive frequency, and identify topological polarization singularities.

Combating Drug Resistance by Exploiting miRNA-200c-Controlled Phase II Detoxification.

Acquired drug resistance constitutes a serious obstacle to the successful therapy of cancer. In the process of therapy resistance, microRNAs can play important roles. In order to combat resistance formation and to improve the efficacy of chemotherapeutics, the mechanisms of the multifaceted hsa-miR-200c on drug resistance were elucidated. Upon knockout of hsa-miR-200c in breast carcinoma cells, a proteomic approach identified altered expression of glutathione S-transferases (GSTs) when cells were treated with the chemotherapeutic drug doxorubicin. In different hsa-miR-200c expression systems, such as knockout, inducible sponge and inducible overexpression, the differential expression of all members of the GST family was evaluated. Expression of hsa-miR-200c in cancer cells led to the repression of a multitude of these GSTs and as consequence, enhanced drug-induced tumor cell death which was evaluated for two chemotherapeutic drugs. Additionally, the influence of hsa-miR-200c on the glutathione pathway, which is part of the phase II detoxification mechanism, was investigated. Finally, the long-term effects of hsa-miR-200c on drug efficacy were studied in vitro and in vivo. Upon doxycycline induction of hsa-miR-200c, MDA-MB 231 xenograft mouse models revealed a strongly reduced tumor growth and an enhanced treatment response to doxorubicin. A combined treatment of these tumors with hsa-miR-200c and doxorubicin resulted in complete regression of the tumor in 60% of the animals. These results identify hsa-miR-200c as an important player regulating the cellular phase II detoxification, thus sensitizing cancer cells not expressing this microRNA to chemotherapeutics and reversing drug resistance through suppression of GSTs.

Fluctuating nanomechanical system in a high finesse optical microcavity.

The idea of extending cavity quantum electrodynamics experiments to sub-wavelength sized nanomechanical systems has been recently proposed in the context of optical cavity cooling and optomechanics of deformable cavities. Here we present an experiment involving a single nanorod consisting of about 10(9) atoms precisely positioned into the confined mode of a miniature high finesse Fabry-Pérot microcavity. We show that the optical transmission of the cavity is affected not only by the static position of the nanorod but also by its vibrational fluctuation. The Brownian motion of the nanorod is resolved with a displacement sensitivity of 200 fm/square root Hz at room temperature. Besides a broad range of sensing applications, cavity-induced manipulation of optomechanical nanosystems and back-action is anticipated.

Development of a tissue-engineered skin substitute on a base of human amniotic membrane.

Allogenic graft material and tissue engineering have recently shown promising results for the improvement of both esthetic and functional outcomes in the treatment of large skin defects. We chose human amniotic membrane as a cellular scaffold in order to develop a skin substitute for later in vivo uses. Various methods of de-epithelialization of the human amniotic membrane were evaluated by histological analysis including hematoxylin-eosin and laminin staining, optic coherence tomography, and scanning electron microscopy with 0.25/0.02% trypsin/ethylenediaminetetraacetic acid treatment and mechanical cell removal showing an almost complete loss of the epithelium and a mainly intact basement membrane. Novel examination of human amniotic membrane by optic coherence tomography was feasible, but difficulties were experienced in handling and interpretation of the tissue as no comparable data exist. Subsequently, we developed an air-liquid interface cell culture to cultivate keratinocytes and fibroblasts on the de-epithelialized human amniotic membrane. We achieved a mostly keratinized surface on the epidermal side with a confluent fibroblast network on the chorion side.

Tracing cell lineages in videos of lens-free microscopy.

In vitro experiments with cultured cells are essential for studying their growth and migration pattern and thus, for gaining a better understanding of cancer progression and its treatment. Recent progress in lens-free microscopy (LFM) has rendered it an inexpensive tool for label-free, continuous live cell imaging, yet there is only little work on analysing such time-lapse image sequences. We propose (1) a cell detector for LFM images based on fully convolutional networks and residual learning, and (2) a probabilistic model based on moral lineage tracing that explicitly handles multiple detections and temporal successor hypotheses by clustering and tracking simultaneously. (3) We benchmark our method in terms of detection and tracking scores on a dataset of three annotated sequences of several hours of LFM, where we demonstrate our method to produce high quality lineages. (4) We evaluate its performance on a somewhat more challenging problem: estimating cell lineages from the LFM sequence as would be possible from a corresponding fluorescence microscopy sequence. We present experiments on 16 LFM sequences for which we acquired fluorescence microscopy in parallel and generated annotations from them. Finally, (5) we showcase our methods effectiveness for quantifying cell dynamics in an experiment with skin cancer cells.

Vemurafenib resistance signature by proteome analysis offers new strategies and rational therapeutic concepts.

The FDA-approved BRAF inhibitor vemurafenib achieves outstanding clinical response rates in patients with melanoma, but early resistance is common. Understanding the pathologic mechanisms of drug resistance and identification of effective therapeutic alternatives are key scientific challenges in the melanoma setting. Using proteomic techniques, including shotgun analysis and 2D-gel electrophoresis, we identified a comprehensive signature of the vemurafenib-resistant M24met in comparison with the vemurafenib-sensitive A375 melanoma cell line. The resistant cells were characterized by loss of differentiation, induction of transformation, enhanced expression of the lysosomal compartment, increased potential for metastasis, migration, adherence and Ca2(+) ion binding, enhanced expression of the MAPK pathway and extracellular matrix proteins, and epithelial-mesenchymal transformation. The main features were verified by shotgun analysis with QEXACTIVE orbitrap MS, electron microscopy, lysosomal staining, Western blotting, and adherence assay in a VM-1 melanoma cell line with acquired vemurafenib resistance. On the basis of the resistance profile, we were able to successfully predict that a novel resveratrol-derived COX-2 inhibitor, M8, would be active against the vemurafenib-resistant but not the vemurafenib-sensitive melanoma cells. Using high-throughput methods for cell line and drug characterization may thus offer a new way to identify key features of vemurafenib resistance, facilitating the design of effective rational therapeutic alternatives.