by Dr Ann-Christin Niehoff
Multimodal imaging by mass spectrometry offers a spatially resolved analysis of tissue sections as an additional tool in clinical research. Here, matrix-assisted laser desorption/ionization mass spectrometry for molecular imaging and laser ablation inductively coupled plasma mass spectrometry for elemental imaging are used to tackle two drug applications.
Mass spectrometry imaging
In recent years, mass spectrometry imaging (MSI) has gained more and more interest in the field of clinical, biological and pharmaceutical research. In contrast to hyphenated chromatographic techniques (e.g. LC-MS or GC-MS), MSI provides spatially resolved information while maintaining high sensitivity. With today’s techniques, high spatial resolution down to the low micrometre range can be achieved and is therefore a good combination with existing clinical imaging approaches from pathology.
Multimodal imaging describes the combination of different imaging techniques, as none by itself is a gold standard to answer all questions. Since MSI works with tissue sections, it can be combined easily with various microscopy applications, providing an additional input to clinical histology. Although protocols for different kinds of tissue sections exist, the preference here is to work on cryosections rather than formalin-fixed paraffin-embedded sections; this helps to avoid wash out of analytes from the tissue during the fixation and embedding steps.
Different MSI techniques can be used to focus on molecular or elemental imaging. In this article, the focus will be on matrixassisted laser desorption ionization mass spectrometry (MALDIMS) for molecular and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) for elemental imaging.
MALDI-MSI
MALDI-MS is the most frequently used imaging technique in molecular MS. The analysis requires coating of the tissue section with a matrix, typically a small organic compound, and performing soft ionization of desorbed molecules by a pulsed laser. Ionization efficiency is highly dependent on molecular structure, matrices and laser wavelength. By scanning over the sample, a full mass spectrum is generated for each pixel.
Using the tandem MS (MS/MS) mode, fragmentation studies can provide information on molecular structures. Matrix preparation is one of the critical aspects and a potential disadvantage of MALDI-MS, Microscopy and Imaging in the Clinical Lab June 2020 21 | Figure1. Multimodal imaging of myocardial infarction Microscopic images of the two parallel sections (a & b) with the area of myocardial infarct (marked with a black line), quantified distribution of gadolinium determined with LA-ICP-MS (c) at 15|μm spot size, distribution of the ligand from Gadofluorine P (d) at 40|μm spot size, as well as the structure of the ligand and the theoretical spectrum (cyan bars) and the measured spectra (black line) with MALDI-MS (e). as it may influence limits of detection and spatial resolution due to analyte extraction of the sample by the matrix. Different instruments for matrix preparation are therefore commercially available to improve homogenous distribution and reproducibility. Owing to matrix effects in molecular MS, quantification is challenging, but is possible to achieve for single analytes via internal standards or standard addition with matrix matched standards.
Here, matrix was sublimated using the iMLayer (Shimadzu). MALDI-MS experiments were performed with the iMScope TRIO (Shimadzu), equipped with a fluorescence microscope, atmospheric pressure MALDI-source and an ion trap/time-of-flight (IT-TOF) mass analyser. IMAGEREVEAL MS (Shimadzu) was used for data analysis.
LA-ICP-MSI
In the field of elemental MSI, LA-ICP-MS provides major, minor and trace elemental information on surfaces and tissue sections. A laser is scanned over the sample and the ablated material is transported by a carrier gas into the ICP source, where the particles are atomized and ionized. To obtain spatially resolved images, transient signals of the respective analyte are required.
As mass analyser, quadrupoles are most frequently used. Although less matrix dependent than MALDI-MS, a fundamental aspect of recent research is method development for reliable quantification strategies, mainly via matrix matched standards. The major disadvantages of LA-ICP-MS are its destructive nature with loss of molecular information.
In this study, experiments were performed with the LSX-G2+ laser ablation system (Teledyne Cetac Technologies) coupled to the quadrupole based ICPMS-2030 (Shimadzu).
Complementary bioimaging of Gadofluorine P in myocardial infarction in mice
Magnetic resonance imaging is a widely used imaging technique in daily clinical practice. To enhance contrast during this examination, several different contrast agents are available. While most gadoliniumbased contrast agents (GBCAs) distribute systemically, some targetspecific GBCAs are under investigation as well. Gadofluorine P is one of these target-specific contrast agents and shows high affinity towards the collagen-rich extracellular matrix which is secreted in the event of myocardial infarction (MI) [1].
In this application, mice underwent injection of Gadofluorine P solution as contrast agents 6|weeks after an induced MI. Afterwards the mice were sacrificed and the hearts were removed for cryosections preparation. By multimodal imaging, LA-ICP-MS was used to generate quantified elemental imaging of gadolinium, while MALDI-MS validated the findings (Fig. 1) and could further provide information for phospholipids and heme b distribution (data not shown).
Figure 1 shows the microscopic images (a & b) of the two thin sections analysed. With LA-ICP-MS (c), a homogeneous distribution of the gadolinium in the healthy myocardium with an average concentration of about 50|μg/g was detected. The infarct region contained two times higher gadolinium concentrations of about 110|μg/g with maximum values up to 370|μg/g.
Higher gadolinium concentrations could also be found in the ventricle due to the intravenous administration of the contrast agent. These distributions could be verified with MALDI-MS imaging (d).
In this experiment, only the protonated ligand of Gadofluorine P rather than the intact complex could be detected (e). The main peak (m/z 1168.39) was used to create the image, which showed good correlation to the gadolinium distribution determined with LA-ICP-MS. The highest intensities of the molecular probe were found in MI and ventricle regions, whereas healthy myocardium showed low and homogenous intensities.
Multimodal imaging of photosensitizers in 3D tumour cell models
Photodynamic therapy offers an alternative cancer treatment. A photosensitive compound (photosensitizer; PS) is administered and the tumour is subsequently irradiated. The activation of the PS leads to the formation of a reactive oxygen species and subsequently to cell apoptosis. One main challenge in the development of PS is the hydrophobic character of the compounds, which hinders tissue penetration. Additionally, the orally administered compound needs to pass through the mucus layer in the gastrointestinal tract. Thus, the determination of the penetration depth of these compounds is of great interest.
The use of 3D tumour spheroids enables in vitro drug screening, while simulating the tumour environment better than 2D cell cultures. The photosensitizer 5,10,15,20-tetrakis (3-hydroxy-phenyl)-porphyrin (mTHPP) and its palladiumtagged analogue mTHPP-Pd were analysed in this study. Here, multimodal imaging is used to visualize the penetration depth of mTHPP and the lipid distribution in 3D tumour spheroid by MALDI-MS (5|μm spot size) as well as to quantify the drug by LA-ICP-MS (7|μm spot size) [2,3].
The MALDI-MS and LA-ICP-MS images of a tumour spheroid treated with mTHPP or mTHPP-Pd are shown in Figure 2. In the microscopic image, an almost spherical tissue section with a diameter of approx. 550|μm can be seen. The distribution map of mTHPP shows a ring-shaped distribution, which can be precisely correlated with the outer cell layer of the tumour spheroid. The PS is distributed homogeneously inside the outer layer and not around the spheroid, although it does not penetrate deeper into the tissue.
Nevertheless, the MALDI-MS experiments revealed that the PS can be detected as an intact molecule without substantial decomposition during the sample preparation. The LA-ICP-MS results for a spheroid incubated with mTHPP-Pd show the same distribution as the mTHPP detected by MALDI-MS. Since the metal-tagged PS is needed for ICP-MS analysis, only spheroids treated with this compound could be investigated. Conversely, this modification of the molecule could no longer be detected using MALDI-MS. Owing to the loading with palladium, the preferred protonation sites of the molecule are unavailable, impairing the detection.
However, before LA-ICP-MS experiments, MALDI-MS can be used to identify phospholipids as shown in Figure 3. Palladium concentrations up to 10|μg/g with an average of 1.9|μg/g were detected (Fig. 3b). This represents an enrichment of PS by a factor of 3 (average) up to 18 (highest concentration) compared to the incubation concentration. The phospholipids PC(34:1), PC(34:0) and PC(30:0) could be detected and show different distributions coherent with the different metabolic zones in a tumour spheroid.
Conclusion
In conclusion, the two applications shown provide an example of how to add MSI to clinical research. Multimodal imaging has successfully been performed to address drug penetration and enrichment in different kinds of tissue based on the combination of elemental imaging and molecular imaging by LA-ICP-MS and MALDI-MS.
The author
Ann-Christin Niehoff PhD
European Innovation Center, Shimadzu Europa GmbH,
47259 Duisburg, Germany

E-mail: acn@shimadzu.eu

Researchers at Rady Children’s Institute for Genomic Medicine (RCIGM) have utilized automated machine-learning and clinical natural language processing (CNLP) to diagnose rare genetic diseases in record time. This new method is speeding answers to physicians caring for infants in intensive care and opening the door to increased use of genome sequencing as a first-line diagnostic test for babies with cryptic conditions.

“Some people call this artificial intelligence, we call it augmented intelligence,” said Stephen Kingsmore, MD, DSc, President and CEO of RCIGM. “Patient care will always begin and end with the doctor. By harnessing the power of technology, we can quickly and accurately determine the root cause of genetic diseases. We rapidly provide this critical information to intensive care physicians so they can focus on personalizing care for babies who are struggling to survive.”

The workflow and research were led by the RCIGM team in collaboration with leading technology and data-science developers —Alexion, Clinithink, Diploid, Fabric Genomics and Illumina.

Dr. Kingsmore’s team has pioneered a rapid Whole Genome Sequencing process to deliver genetic test results to neonatal and paediatric intensive care (NICU/PICU) physicians to guide medical intervention. RCIGM is the research arm of Rady Children’s Hospital-San Diego.

By reducing the need for labour-intensive manual analysis of genomic data, the supervised automated pipeline provided significant time-savings. In February 2018, the same team achieved the Guinness World Record for fastest diagnosis through whole genome sequencing. Of the automated runs, the fastest times – averaging 19 hours – were achieved using augmented intelligence.

“This is truly pioneering work by the RCIGM team—saving the lives of very sick newborn babies by using AI to rapidly and accurately analyse their whole genome sequence “ says Eric Topol, MD, Professor of Molecular Medicine at Scripps Research and author of the new book Deep Medicine.

RCIGM has optimized and integrated several time-saving technologies into a rapid Whole Genome Sequencing (rWGS) process to screen a child’s entire genetic makeup for thousands of genetic anomalies from a blood sample.

Key components in the rWGS pipeline come from Illumina, the global leader in DNA sequencing, including Nextera DNA Flex library preparation, whole genome sequencing via the NovaSeq 6000 and the S1 flow cell format. Speed and accuracy are enhanced by Illumina’s DRAGEN (Dynamic Read Analysis for GENomics) Bio-IT Platform.

Other pipeline elements include Clinithink’s clinical natural language processing platform CliX ENRICH that quickly combs through a patient’s electronic medical record to automatically extract comprehensive patient phenotype information.

Another core element of the machine learning system is MOON by Diploid. The platform automates genome interpretation using AI to automatically filter and rank likely pathogenic variants. Deep phenotype integration, based on natural language processing of the medical literature, is one of the key features driving this automated interpretation. MOON takes five minutes to suggest the causal mutation out of the 4.5 million variants in a whole genome.

In addition, Alexion’s rare disease and data science expertise enabled the translation of clinical information into a computable format for guided variant interpretation.

As part of this study, the genetic sequencing data was fed into automated computational platforms under the supervision of researchers. For comparison and verification, clinical medical geneticists on the team used Fabric Genomics’ AI-based clinical decision support software, OPAL (now called Fabric Enterprise)—to confirm the output of the automated pipeline. Fabric software is part of RCIGM’s standard analysis and interpretation workflow.

The study titled “Diagnosis of genetic diseases in seriously ill children by rapid whole-genome sequencing and automated phenotyping and interpretation,” found that automated, retrospective diagnoses concurred with expert manual interpretation (97 percent recall, 99 percent precision in 95 children with 97 genetic diseases).

Researchers concluded that genome sequen-cing with automated phenotyping and interpretation—in a median 20:10 hours—may spur use in intensive care units, thereby enabling timely and precise medical care. “Using machine-learning platforms doesn’t replace human experts. Instead it augments their capabilities,” said Michelle Clark, PhD, statistical scientist at RCIGM and the first author of the study. “By informing timely targeted treatments, rapid genome sequencing can improve the outcomes of seriously ill children with genetic diseases.”
Rady Children’s Institutewww.radygenomics.org/category/news/pr/

BioCity, a life science incubator and business collective has released its biennial publication, the UK Life Science Start-Up Report, an in-depth analysis of emerging businesses within the life sciences across the UK.
The report looks at the prevalence of life science start-ups in the UK over the past five years and the broader landscape in which they operate to also asses the quality of UK life science start-ups.
The report documents an unprecedented period of growth for the life sciences, thanks in part to a change in the funding landscape, expressed in a four-fold increase to £2.8 billion of investment in early-stage ventures, compared to the previous five-year period.
Multiple factors are highlighted as driving this expansion, but of greatest impact was Industry news January 2020 11 | the emergence of a number of significant venture funds able and willing to make very large investments in early stage businesses. Also identified as a contributing factor is the increasing use of smaller companies and academia as sources of innovation by large pharma companies aiming to counteract falling R&D productivity. Simultaneously, many universities such as Bristol, Newcastle and Aberdeen introduced a gear change in spin-out formation.
Author of the report, Dr Glenn Crocker said: “Both the number of companies starting up and the amount invested in them has taken off. We have seen a 50% increase in the number of companies and a four-fold increase in investment going into them; this will likely result in a substantial increase in the demand for space. We estimate that this cohort of businesses alone could require 1.4 million sq ft of specialist facilities over the next five years. One consequence of this demand growth is that real estate investors are being increasingly attracted to the sector.”

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