Background-suppressed SRS fingerprint imaging with a fully integrated system using a single optical parametric oscillator

Frequency-modulation stimulated Raman scattering microscopy with an acousto-optic tunable filter

Stimulated Raman scattering (SRS) microscopy is increasingly employed for highly specific, label-free, and high-speed bioimaging. Despite its benefits, SRS is susceptible to spurious background signals caused by competing effects, which lower the possible imaging contrast and sensitivity. An efficient approach to suppress these undesired background signals is frequency-modulation (FM) SRS, which exploits the competing effects' weak spectral dependence compared to the SRS signal's high spectral specificity. We propose an FM-SRS scheme realized with an acousto-optic tunable filter, which presents a few advantages compared to other solutions presented in the literature. In particular, it can perform automated measurements from the fingerprint to the CH-stretching region of the vibrational spectrum without any manual adjustment of the optical setup. Moreover, it allows simple all-electronic control of the spectral separation and relative intensities of the pair of probed wavenumbers.

Frequency modulation stimulated Raman scattering scheme for real-time background correction with a single light source

A frequency modulation (FM) scheme for stimulated Raman scattering (SRS) is presented with a single fiber-based light source. Pulse-to-pulse wavelength-switching allows real-time subtraction of parasitic signals leaving only the resonant SRS signal with a noise reduction of up to 30 % compared to digital subtraction schemes, leading effectively to a contrast improvement by a factor of up to 8.3. The wide tuning range of the light source from 1500 cm^-1 to 3000 cm^-1 and the possibility to separately adjust the resonant and the nonresonant wavenumber for every specimen allow to investigate a variety of samples with high contrast and high signal-to-noise ratio, e. g., for medical diagnostics.

Discriminating cell line specific features of antibiotic-resistant strains of Escherichia coli from Raman spectra via machine learning analysis

While Raman spectroscopy can provide label-free discrimination between highly similar biological species, the discrimination is often marginal, and optimal use of spectral information is imperative. Here, we compare two machine learning models, an artificial neural network and a support vector machine, for discriminating between Raman spectra of 11 bacterial mutants of Escherichia coli MDS42. While we find that both models discriminate the 11 bacterial strains with similarly high accuracy, sensitivity and specificity, it is clear that the models form different class boundaries. By extracting strain-specific (and function-specific) spectral features utilized by the models, we find that both models utilize a small subset of high intensity peaks while separate subsets of lower intensity peaks are utilized by only one method or the other. This analysis highlights the need for methods to use the complete spectral information more effectively, beginning with a better understanding of the distinct information gained from each model.

SRS-FISH: A high-throughput platform linking microbiome metabolism to identity at the single-cell level

One of the biggest challenges in microbiome research in environmental and medical samples is to better understand functional properties of microbial community members at a single-cell level. Single-cell isotope probing has become a key tool for this purpose, but the current detection methods for determination of isotope incorporation into single cells do not allow high-throughput analyses. Here, we report on the development of an imaging-based approach termed stimulated Raman scattering-two-photon fluorescence in situ hybridization (SRS-FISH) for high-throughput metabolism and identity analyses of microbial communities with single-cell resolution. SRS-FISH offers an imaging speed of 10 to 100 ms per cell, which is two to three orders of magnitude faster than achievable by state-of-the-art methods. Using this technique, we delineated metabolic responses of 30,000 individual cells to various mucosal sugars in the human gut microbiome via incorporation of deuterium from heavy water as an activity marker. Application of SRS-FISH to investigate the utilization of host-derived nutrients by two major human gut microbiome taxa revealed that response to mucosal sugars tends to be dominated by Bacteroidales, with an unexpected finding that Clostridia can outperform Bacteroidales at foraging fucose. With high sensitivity and speed, SRS-FISH will enable researchers to probe the fine-scale temporal, spatial, and individual activity patterns of microbial cells in complex communities with unprecedented detail.

Spectral focusing in picosecond pulsed stimulated Raman scattering microscopy

We introduce spectral focusing of picosecond laser pulses in stimulated Raman scattering (SRS) microscopy to improve spectral resolution, reduce nonlinear background signals, and decrease nonlinear photodamage. We produce a pair of 14 ps pump and Stokes laser pulses by spectral focusing of a 2 ps laser and achieve a spectral resolution of 2 cm^-1. Due to instantaneous narrow-band excitation, we find that the chirped 14 ps laser pulses can be used to improve the signal-to-background ratio in SRS microscopy of various samples such as polymer particles and small molecules in HeLa cells. The lower peak powers produced by chirped picosecond laser pulses also reduce nonlinear photodamage, allowing long-term SRS imaging of living cells with higher SNR.

Practical considerations for quantitative and reproducible measurements with stimulated Raman scattering microscopy

This tutorial review presents the most important practical considerations for sample preparation, instrument set-up, image acquisition and data analysis to obtain reproducible SRS measurements.

Shot-noise limited tunable dual-vibrational frequency stimulated Raman scattering microscopy

We present a shot-noise limited SRS implementation providing a >200 mW per excitation wavelength that is optimized for addressing two molecular vibrations simultaneously. As the key to producing a 3 ps laser of different colors out of a single fs-laser (15 nm FWHM), we use ultra-steep angle-tunable optical filters to extract 2 narrow-band Stokes laser beams (1-2 nm & 1-2 ps), which are separated by 100 cm^-1. The center part of the fs-laser is frequency doubled to pump an optical parametric oscillator (OPO). The temporal width of the OPO's output (1 ps) is matched to the Stokes beams and can be tuned from 650-980 nm to address simultaneously two Raman shifts separated by 100 cm^-1 that are located between 500 cm^-1 and 5000 cm^-1. We demonstrate background-free SRS imaging of C-D labeled biological samples (bacteria and Drosophila). Furthermore, high quality virtual stimulated Raman histology imaging of a brain adenocarcinoma is shown for pixel dwell times of 16 µs.

Simultaneous stimulated Raman gain and loss detection (SRGAL)

The fidelity of stimulated Raman scattering (SRS) microscopy images is impaired by artifacts such as thermal lensing, cross-phase modulation and multi-photon absorption. These artifacts affect differently the stimulated Raman loss (SRL) and stimulated Raman gain (SRG) channels making SRL and SRG image comparisons attractive to identify and correct SRS image artifacts. To provide answer to the question: "Can I trust my SRS images?", we designed a novel, but straightforward SRS scheme that enables the dectection of the stimulated Raman gain and loss (SRGAL) simultaneously at the same pixel level. As an advantage over the conventional SRS imaging scheme, SRGAL doubles the SRS signal by acquiring both SRL as well as SRG and allows for the identification of SRS artifacts and their reduction via a balanced summation of the SRL and SRG images.