Research progress of nano-scale secondary ion mass spectrometry (NanoSIMS) in soil science: Evolution, applications, and challenges

Li, Qi; Chang, Jingjing; Li, Linfeng; Lin, Xiaoyang; Li, Yichun

doi:10.1016/j.scitotenv.2023.167257

Cited by 8 publications

(2 citation statements)

References 119 publications

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“… 50 This significant advancement allows for enhanced analysis and precise measurement of isotope ratios in diverse samples. 51 Nano-SIMS has a broad range of applications in tracking both endogenous elements, including Cu, Zn, N, S, and P, and metallodrugs such as platinum- 52 and ruthenium-based 53 anticancer drugs. The application of Nano-SIMS for a wide range of elemental analysis provides information on the distribution, localization, and interaction of metallodrugs with cellular components at the nanoscale, 52,53 providing a deeper understanding of the behavior of these drugs within cells.…”

Section: Recent Advances In Metal-detection Based Techniquesmentioning

confidence: 99%

Metal-detection based techniques and their applications in metallobiology

Zhou,

Li,

Tse

et al. 2024

Chem. Sci.

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Section: Recent Advances In Metal-detection Based Techniquesmentioning

confidence: 99%

Metal-detection based techniques and their applications in metallobiology

Zhou,

Li,

Tse

et al. 2024

Chem. Sci.

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“…NanoSIMS uses a focused ion beam to produce secondary ions from a sample surface that are subsequently analyzed via a double focusing mass spectrometer to attain spatially resolved elemental and isotopic information (19,20). Although NanoSIMS is capable of detecting isotopes at a much greater sensitivity and spatial resolution (≥50 nm) than Raman, it is destructive to the sample and provides limited molecular information (21).…”

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confidence: 99%

Comparing Raman and NanoSIMS for heavy water labeling of single cells

Schaible,

Cliff,

Crandall

et al. 2024

Preprint

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Stable isotope probing (SIP) experiments in conjunction with Raman microspectroscopy (Raman) or nano-scale secondary ion mass spectrometry (NanoSIMS) are frequently used to explore single cell resolved metabolic activity in pure cultures as well as complex microbiomes. Despite the increasing popularity of these techniques, no study has yet compared results from isotope incorporation measurements using both Raman and NanoSIMS directly on the same cell. This knowledge gap creates uncertainty about the comparability of single cell SIP data generated independently using these techniques. In this study, we conducted a comparative analysis of 543Escherichia colicells grown in M9 minimal medium in the absence or presence of heavy water (2H2O) at single cell resolution using correlative Raman and NanoSIMS measurements. For the first time, we were able to establish the extent of data equivalence, allowing for comparisons between the two approaches. Utilizing the dataset from this study, we examined the effectiveness of preprocessing techniques and optimal wavenumbers for analyzing Raman spectra, along with identifying the ideal masses for NanoSIMS analysis of cells incubated in the presence of2H2O. We make recommendations for approaches to analyzing and comparing data using both or either of these techniques. We anticipate that the findings presented herein will enhance the comparability of studies employing either technique and ultimately contribute to the establishment of a standardized framework within the field.ImportanceAccurate and reliable measurements of cellular properties are fundamental to understanding the function and activity of microbes. This study addresses to what extent Raman microspectroscopy and nano-scale secondary ion mass spectrometry (NanoSIMS) measurements of single cell anabolic activity can be compared. For the first time, we study the relationship of the incorporation of a stable isotope (2H through incorporation of2H2O) as determined by the two techniques and calculate a correlation coefficient to support the use of either technique when analyzing cells incubated with2H2O. The ability to discern between the comparative strengths and limitations of these techniques is invaluable in refining experimental protocols, enhancing data comparability between studies, data interpretation, and ultimately advancing the quality and reliability of outcomes in microbiome research.

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