Bioremediation potential of cadmium by recombinant Escherichia coli surface expressing metallothionein MTT5 from Tetrahymenathermophila.

Cadmium (Cd) is a common heavy metal contaminant in industrial wastewater that causes many diseases in humans. Metallothionein (MT), a cysteine-rich metal-binding protein, is well known in chelate-heavy metals. In this study, we expressed MTT5 of Tetrahymena thermophila fused with Lpp-OmpA in the outer membrane of Escherichia coli to determine its ability to accumulate and adsorb Cd. Our results revealed that our recombinant E. coli had a 4.9-fold greater Cd adsorption compared to wild E. coli. Adsorption isothermic analysis demonstrated that the adsorption behavior for Cd in our recombinant bacteria was better fitted into the Freundlich isotherm model than Langmuir isotherm model. Fourier-transform infrared spectroscopy indicated that phosphate and organic phosphate groups were involved in the interaction between Cd and the bacterial surface. Using quantitative reverse transcription polymerase chain reaction, we further showed that the expression of metal-resistance genes (dnaK and clpB) was downregulated due to surface MTT5 protected our recombinant bacteria from Cd2+ adsorption. Furthermore, we showed that our recombinant bacteria could adsorb Cd from the contaminated wastewater containing other metals and were suggested to be applied in the field study.

Isolation of TTF-1 Positive Circulating Tumor Cells for Single-Cell Sequencing by Using an Automatic Platform Based on Microfluidic Devices.

Single-cell sequencing provides promising information in tumor evolution and heterogeneity. Even with the recent advances in circulating tumor cell (CTC) technologies, it remains a big challenge to precisely and effectively isolate CTCs for downstream analysis. The Cell RevealTM system integrates an automatic CTC enrichment and staining machine, an AI-assisted automatic CTC scanning and identification system, and an automatic cell picking machine for CTC isolation. H1975 cell line was used for the spiking test. The identification of CTCs and the isolation of target CTCs for genetic sequencing were performed from the peripheral blood of three cancer patients, including two with lung cancer and one with both lung cancer and thyroid cancer. The spiking test revealed a mean recovery rate of 81.81% even with extremely low spiking cell counts with a linear relationship between the spiked cell counts and the recovered cell counts (Y = 0.7241 × X + 19.76, R2 = 0.9984). The three cancer patients had significantly higher TTF-1+ CTCs than healthy volunteers. All target CTCs were successfully isolated by the Cell Picker machine for a subsequent genetic analysis. Six tumor-associated mutations in four genes were detected. The present study reveals the Cell RevealTM platform can precisely identify and isolate target CTCs and then successfully perform single-cell sequencing by using commercially available genetic devices.

An Automatic Platform Based on Nanostructured Microfluidic Chip for Isolating and Identification of Circulating Tumor Cells.

Circulating tumor cell (CTC) test is currently used as a biomarker in cancer treatment. Unfortunately, the poor reproducibility and limited sensitivity with the CTC detection have limited its potential impact on clinical application. A reliable automated CTC detection system is therefore needed. We have designed an automated microfluidic chip-based CTC detection system and hypothesize this novel system can reliably detect CTC from clinical specimens. SKOV3 ovarian cancer cell line was used first to test the reliability of our system. Ten healthy volunteers, 5 patients with benign ovarian tumors, and 8 patients with epithelial ovarian cancer (EOC) were recruited to validate the CTC capturing efficacy in the peripheral blood. The capture rates for spiking test in SKOV3 cells were 48.3% and 89.6% by using anti-EpCAM antibody alone and a combination of anti-EpCAM antibody and anti-N-cadherin antibody, respectively. The system was sensitive to detection of low cell count and showed a linear relationship with the cell counts in our test range. The sensitivity and specificity were 62.5% and 100% when CTC was used as a biomarker for EOC. Our results demonstrated that this automatic CTC platform has a high capture rate and is feasible for detection of CTCs in EOC.