The novel compound — a polyamine — seems to destroy Staphylococcus aureus, the bacterium that causes (among other things) deadly Methicillin-resistant Staphylococcus aureus (MRSA) infections, by disrupting the pathogen’s cell membrane.

The compound was tested in-vitro against 10 different antibiotic-resistant strains of S. aureus, including some that are known to be resistant to vancomycin — the final drug of choice given to patients fighting an MRSA infection. The compound was completely successful against all strains, resulting in no further bacterial growth.

The study shows that as well as destroying S. aureus directly, the compound is able to restore the sensitivity of multidrug resistant strains of the bacteria to three important antibiotics (daptomycin, oxacillin and vancomycin). This could mean that antibiotics that have become ineffective through decades of overuse may, in time, reclaim their ability to bring serious infections under control.

“We’re not entirely sure why these synergies occur between the compound and antibiotics, but we’re keen to explore this further,” said Dr Laabei, researcher from the Department of Live Sciences at Bath.

The pathogen’s vulnerability

Polyamines are naturally occurring compounds found in most living organisms. Until a decade ago, they were thought to be essential to all life, but scientists now know they are both absent in, and toxic to, S. aureus. Since making this discovery, researchers have been attempting to exploit the pathogen’s unusual vulnerability to polyamines to inhibit bacterial growth.

Now Dr Laabei and his colleagues have found that a modified polyamine (named AHA-1394) is far more effective at destroying antibiotic-resistant strains of S. aureus than even the most active natural polyamine.

Explaining, Dr Laabei said: “Using our novel compound, the pathogen is destroyed — meaning growth is inhibited — when it’s used at a concentration that’s over 128 times lower than that required to destroy the pathogen when we use a natural polyamine.

“This is important, as drugs that have the lowest minimum inhibitory concentration are likely to be more effective antimicrobial agents, and to be safer to the patient.”

Though further research is needed, Dr Laabei believes the new compound “could have important implications in a clinical setting as a new treatment option.”

He said: “Preliminary research suggests the compound is non-toxic to humans, which of course is essential. In our next study, for which we’re seeking funding, we hope to focus on the precise mechanisms used by the compound to inhibit S. aureus. We believe the compound attacks the membrane of S. aureus, resulting in the membrane becoming permeable, resulting in bacterial death.”

The compound was also tested against biofilm — the thin, hard-to-treat layer of microorganisms that grows on hard surfaces (seen, for instance, as plaque on teeth or a stubborn film on urinary catheters) and can result in serious infection. The results were promising here too, with the compound preventing the formation of new biofilm, though not disrupting established biofilm.

Antibiotic resistance

Antibiotic resistance (or antimicrobial resistance — AMR) poses a major threat to human health around the world, and S. aureus has become one of the most notorious multidrug-resistant pathogens.

A recent study looking back at the health effects of AMR in 2019 finds the pathogen was associated with one-million deaths worldwide, as a result of infections not responding to antibiotics.

S. aureus is found in 30% of the population, living in people’s nasal passages and on the skin, and mostly it does not cause infection. Until quite recently, an MRSA infection was regarded as a hospital problem, and those affected were mostly people with an already compromised immune system. Over the past 20 years, however, for complex and only partially understood reasons, there has been an upswing in community-wide infections even among otherwise healthy individuals, bringing a sense of urgency to the quest to find fresh ways to tackle the problem.

“New treatments are urgently needed to treat infections,” said Dr Laabei.

The study, published in Cell Reports Medicine, built on ongoing collaborative Cleveland Clinic research to support further investigation into metformin as a drug repurposing candidate. Researchers used advanced computation and genetic sequencing to determine that metformin’s targets overlap significantly with genes dysregulated in atrial fibrillation.

“Finding drugs or procedures to treat atrial fibrillation is difficult because of potential serious side effects,” said Mina Chung, M.D., senior author of the study who is in Cleveland Clinic’s Department of Cardiovascular Medicine in the Heart, Vascular and Thoracic Institute. “There is a significant need for new treatments for atrial fibrillation as there have been no new drugs approved in more than a decade.”

“It’s not that we’ve found a new drug target where it takes 20 years to test this in individuals,” said Jessica Castrillon Lal, the study’s first author and a fifth-year graduate student in the Cleveland Clinic Molecular Medicine program.

“We can cut off 10+ years in the drug development pipeline. We already have the information there. We just have to test it in a very computationally efficient way, such as artificial intelligence technology,” said Feixiong Cheng, Ph.D., co-senior author of the study who is Associate Staff at the Genomic Medicine Institute in Cleveland Clinic’s Lerner Research Institute.

The analysis found metformin targeted 30 genes associated with atrial fibrillation, with direct effects on gene expression for eight. Eight other candidate drugs surfaced in the analysis, but researchers were able to identify metformin as the most promising candidate through testing and reviewing outcomes in large stores of patient data.

Castrillon Lal conducts research in Dr. Cheng’s lab, which uses network medicine approaches to find candidate drugs for repurposing, creating vast networks of molecular interactions. For this study, researchers winnowed down a list of 2,800 FDA-approved treatments by analyzing three data sources: a map of interactions between proteins called an “interactome”; a network of genes associated with atrial fibrillation; and each medicine’s molecular or genetic targets.

Atrial fibrillation is the most common type of heart arrhythmia in the world and can lead to complications, including stroke and heart failure. Treatments have been primarily directed toward trying to prevent the arrhythmia using drugs targeting the electrical system, including ion channels in the heart, or using catheter ablation to isolate the pulmonary veins where initiating beats of atrial fibrillation occur.

However, side effects, limited success and potential complications can limit these approaches.

The research was conducted in collaboration with labs led by Dr. Chung, Dr. Cheng, David Van Wagoner, Ph.D.; Jonathan Smith, Ph.D., Department of Cardiovascular and Metabolic Sciences; and John Barnard, Ph.D., Department of Quantitative Health Sciences in the Lerner Research Institute.

Prior work from Drs. Chung, Smith, Van Wagoner, and Barnard had also identified the enzyme AMPK as a potential key regulator for metabolic stress. Metabolic stress has been associated with atrial fibrillation.

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The study by Professor Loc Do of the University of Queensland Faculty of Health and Behavioural Sciences, School of Dentistry and colleagues examined the effect of early childhood exposures to water fluoridation on measures of school-age executive functioning and emotional and behavioral development in a population-based sample. This longitudinal follow-up study used information from Australia’s National Child Oral Health Study of 2012-14. Children aged 5-10 years at the baseline were contacted again after 7-8 years, before they had turned 18 years of age.

Percent lifetime exposed to fluoridated water (%LEFW) from birth to the age of five years was estimated from residential history and postcode-level fluoride levels in public tap water. Measures of children’s emotional and behavioral development were assessed by the Strength and Difficulties Questionnaire (SDQ), and executive functioning was measured by the Behavior Inventory of Executive Functioning (BRIEF). Multivariable regression models were generated to compare the associations between the exposure and the primary outcomes, controlled for covariates. An equivalence test was also conducted to compare the primary outcomes of those who had 100%LEFW against those with 0%LEFW.

Sensitivity analysis was also conducted. A total of 2,682 children completed SDQ and BRIEF, with mean scores of 7.0 (95%CI: 6.6, 7.4) and 45.3 (44.7, 45.8), respectively. Those with lower %LEFW tended to have poorer scores on the SDQ and BRIEF. Multivariable regression models reported no association between exposure to fluoridated water and the SDQ and BRIEF scores. Low household income, identifying as Indigenous, and having a neurodevelopmental diagnosis were associated with poorer SDQ/BRIEF scores.

The study concluded that exposure to fluoridated water during the first five years of life was not associated with altered measures of child emotional and behavioral development and executive functioning. Children who had been exposed to fluoridated water for their whole early childhood had their measures of emotional, behavioral development and executive functioning at least equivalent to that of children who had no exposure to fluoridated water.

“Water fluoridation is unquestionably effective in preventing dental caries, and this study is an important addition to the body of literature documenting the safety of water fluoridation,” said IADR President Brian O’Connell, Dean of the Faculty of Health Sciences, Trinity College Dublin, Ireland. “The IADR recently reaffirmed its support for water fluoridation as this public health measure has a high benefit/cost ratio and benefits deprived communities the most, thus reducing health inequalities.”

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Brazil presents a key example. The country is home to the world’s largest area of rainforest — some 1.2 million square miles, an area more than 16 times the size of Nebraska. The Amazon contains large tracts of rainforests that, when converted to agriculture, release a huge amount of carbon dioxide into the atmosphere, exacerbating climate change.

Increasing agricultural production is a national priority for Brazil, the world’s largest soybean exporter. Since the 1990s, agricultural encroachment has eroded major areas of the country’s rainforest. During 2015-19, the Amazon basin accounted for a third of the land converted for Brazilian soybean expansion.

A newly released four-year study by the University of Nebraska-Lincoln and its research partners in Brazil identifies a path forward that would allow Brazil to strengthen its agricultural sector while safeguarding the rainforest. The scientists’ recommendations have broad applicability to other developing countries facing a similar challenge.

“In the current context of high grain prices and food supply disruptions, we believe there is a critical need for major crop-producing countries to reassess their potential to produce more on existing cropland,” the authors wrote in an article published Oct. 10 in the journal Nature Sustainability. “Without an emphasis on intensifying crop production within the existing agricultural area, coupled with strong institutions and policies that prevent deforestation in frontier agricultural areas, it would be difficult to protect the last bastions of forests and biodiversity on the planet while being sensitive to the economic aspirations of countries to develop.”

Since 2000, moratoria and incentives have been used to slow deforestation in Brazil. However, sharply increased commodity prices and political pressure to quickly recover from combined impacts of the COVID-19 pandemic and war in Ukraine have placed the Amazonian rainforest under heightened threat. If current trends continue, Brazil will convert about 57 million acres to soybean production in the next 15 years, with about one-fourth of the expansion occurring in environmentally fragile lands such as rainforest and savannah.

Yet prohibiting cropland expansion would cost Brazil an estimated $447 billion in lost economic opportunity through 2035.

The study led by Patricio Grassini, Sunkist Distinguished Professor in Agronomy and associate professor in the Department of Agronomy and Horticulture at Nebraska, shows how it could be possible for Brazil to expand its agricultural production without converting more rainforest and savannah to crops. With a carefully managed strategy to intensify production on existing acres, the country could increase its annual soybean output by 36% by 2035 while reducing greenhouse gas emissions by 58% compared to current trends.

Grassini and his co-authors describe a three-pronged “intensification” strategy that calls for:

* Significantly increasing soybean crop yields. * Growing a second crop of corn on soybean fields in certain areas. * Raising more cattle on smaller pastures to free up more land for soybeans.

Brazil’s tropical and subtropical climates make it possible to cultivate two crops on the same land during the growing season in most regions, Grassini said. Plus, “livestock production is huge in Brazil,” he said, “and our study shows there is a big opportunity for Brazil to increase livestock-based production systems and by doing so, free up some of the area currently used for livestock production and use that land for producing more soy.”

Detailed modeling for the project indicates that by 2035, the strategy could boost Brazil’s soybean production by 36%. At the same time, Grassini said, Brazil could “eliminate deforestation completely and essentially reduce the amount of carbon dioxide equivalents released into the atmosphere, helping to mitigate climate change.”

“This approach strengthens agriculture while protecting fragile ecosystems that are important from a perspective of climate change mitigation as well as biodiversity conservation,” he said.

To determine how much yields could be improved on existing Brazilian farm ground, the scientists examined soybean production in four key regions: the Pampa and the Atlantic Forest regions along the Atlantic coast, where soybean cultivation has been underway for about 50 years, and the Amazon and the Cerrado regions in Brazil’s interior, where soybean production began after the turn of the 21st century. The analysis made extensive use of the Global Yield Gap Atlas previously developed by Grassini and colleagues at Nebraska. The atlas is the world’s leading database on high-quality agronomic data, covering more than 15 major food crops across more than 75 countries.

“By showing that it is possible to produce more on existing agricultural land,” the scientists wrote, “this research study is bringing real solutions to the table and can have a massive impact to help Brazil produce more while protecting the environment.”

Success on the dual goal of agricultural expansion and protecting the forest will require strong institutions, proper policy and enforcement to make sure those productivity gains effectively translate into forest preservation, Grassini cautioned. Still, the intensification approach can help achieve a reasonable balance between crop production and the protection of fragile ecosystems.

Grassini’s team calculated three scenarios in the four key regions: “business as usual,” where existing trends would continue; “no cropland expansion,” where additional land conversion would be prohibited; and “intensification,” where steps would be taken to increase yields, encourage second cropping and concentrate cattle production. They concluded the intensification strategy would enable Brazil to realize 85% of the projected gross income from soybean and second-crop maize, compared to current trends, while reducing global climate warming by 58%.

The four-year project involved collaboration between the University of Nebraska-Lincoln and universities in Brazil, including the University of Sao Paulo, Federal University of Santa Maria and University of Goias, as well as Embrapa, the leading agricultural research organization in Brazil. Coauthors on the project included Juan Pablo Monzon and José F. Andrade, former research assistant professors in agronomy and horticulture at Nebraska. The project was funded by the International Plant Nutrition Institute, Research Foundation of the State of São Paulo, Brazilian Research Council, Research Foundation of the State of Rio Grande do Sul, and the Global Engagement Office in Nebraska’s Institute of Agriculture and Natural Resources through the FAPESP-UNL SPRINT program.

Fabio R. Marin, a Brazilian scientist who was the main author of the paper along with Brazilian scientist Alencar J. Zanon, received financial support from the Fulbright program to support a six-month stay at Nebraska.

But AI models that lack transparency about how and why a diagnosis is made can be problematic. This opaque reasoning — also known “black box” AI — can diminish clinician trust in the reliability of the AI tool and thus discourage its use. This lack of transparency could also mislead clinicians into over-trusting the tool’s interpretation.

In the realm of medical imaging, one way to create more understandable AI models and to demystify AI decision-making have been saliency assessments — an approach that uses heat maps to pinpoint whether the tool is correctly focusing only on the relevant pieces of a given image or homing in on irrelevant parts of it.

Heat maps work by highlighting areas on an image that influenced the AI model’s interpretation. This could help human physicians see whether the AI model focuses on the same areas as they do or is mistakenly focusing on irrelevant spots on an image.

But a new study, published in Nature Machine Intelligence on Oct. 10, shows that for all their promise, saliency heat maps may not be yet ready for prime time.

The analysis, led by Harvard Medical School investigator Pranav Rajpurkar, Matthew Lungren of Stanford, and Adriel Saporta of New York University, quantified the validity of seven widely used saliency methods to determine how reliably and accurately they could identify pathologies associated with 10 conditions commonly diagnosed on X-ray, such as lung lesions, pleural effusion, edema, or enlarged heart structures. To ascertain performance, the researchers compared the tools’ performance against human expert judgment.

In the final analysis, tools using saliency-based heat maps consistently underperformed in image assessment and in their ability to spot pathological lesions, compared with human radiologists.

The work represents the first comparative analysis between saliency maps and human expert performance in the evaluation of multiple X-ray pathologies. The study also offers a granular understanding of whether and how certain pathological characteristics on an image might affect AI tool performance.

The saliency-map feature is already used as a quality assurance tool by clinical practices that employ AI to interpret computer-aided detection methods, such as reading chest X-rays. But in light of the new findings, this feature should be applied with caution and a healthy dose of skepticism, the researchers said.

“Our analysis shows that saliency maps are not yet reliable enough to validate individual clinical decisions made by an AI model,” said Rajpurkar, who is an assistant professor of biomedical informatics at HMS. “We identified important limitations that raise serious safety concerns for use in current practice.”

The researchers caution that because of the important limitations identified in the study, saliency-based heat maps should be further refined before they are widely adopted in clinical AI models.

The team’s full codebase, data, and analysis are open and available to all interested in studying this important aspect of clinical machine learning in medical imaging applications.

Co-authors included Xiaotong Gui, Ashwin Agrawal, Anuj Pareek, Jayne Seekins, Francis Blankenberg, and Andrew Ng, all from Stanford University; Steven Truong and Chanh Nguyen, of VinBrain, Vietnam; and Van-Doan Ngo, of Vinmec International Hospital, Vietnam.

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Under the microscope, researchers often observe different cell types organizing themselves in peculiar patterns within tissues, or sometimes a rare cell type that stands out by occupying a unique position, exhibiting an unusual shape, or expressing a specific biomarker molecule. To determine the deeper meaning of their observations, they have developed approaches to also access cells’ gene expression patterns (transcriptomes) by analyzing the gene-derived RNA molecules present within them, which they can match with cells’ shapes, spatial positions, and molecular biomarkers.

However, these “spatial transcriptomics” approaches still only capture a fraction of a cell’s total RNA molecules, and cannot deliver the depth and quality of analysis provided by single-cell sequencing methods, which were developed to investigate the transcriptomes of individual cells isolated from tissues or biofluids via next-generation sequencing (NGS) techniques. Nor do they allow researchers to only home in on specific cells based on their location in a tissue, which would greatly facilitate the pursuit of disjointed cell populations, or rare, difficult-to-isolate cells like rare brain cells with unique functions, or immune cells that invade tumors. In addition, because the original tissue environment is disrupted, many spatial transcriptomics and all single-cell sequencing methods prevent researchers from revisiting their samples to perform follow-up analysis, and they are costly because they require specialized instruments or reagents.

A new advance made at the Wyss Institute for Biologically Inspired Engineering at Harvard University now overcomes these limitations with a DNA nanotechnology-driven method called “Light-Seq.” Light-Seq allows researchers to “geotag” the full repertoire of RNA sequences with unique DNA barcodes exclusive to a few cells of interest. These target cells are selected using light under a microscope via a fast and effective photocrosslinking process.

With the help of a new DNA nanotechnology, the barcoded RNA sequences are then translated into coherent DNA strands, which can then be collected from the tissue sample and identified using NGS. The Light-Seq process can be repeated with different barcodes for different cell populations within the same sample, which is left intact for follow-up analysis. With a performance comparable to single-cell sequencing methods, it significantly broadens the depth and scope of investigations possible on a tissue sample. The method is published in Nature Methods[BB1] .

“Light-Seq’s unique combination of features fills an unmet need: the ability to perform imaging-informed, spatially prescribed, deep-sequencing analysis of hard, if not impossible-to-isolate cell populations or rare cell types in preserved tissues, with one-to-one correspondence of their highly refined gene expression state with spatial, morphological, and potentially disease-relevant features,” said Peng Yin, Ph.D., one of four corresponding authors and a Core Faculty member at the Wyss Institute, where his group developed Light-Seq. “It thus has potential to fast-forward the biological discovery process in various biomedical research areas.” Yin is also a Professor of Systems Biology at Harvard Medical School (HMS).

From barcoding in situ to sequencing ex situ

The Light-Seq project was spearheaded by Jocelyn (Josie) Kishi, Ph.D., Sinem Saka, Ph.D., and Ninning Liu, Ph.D. in Yin’s group at the Wyss, and Emma West, Ph.D. in Constance Cepko’s lab at HMS. Previously, Kishi and Saka had developed SABER-FISH as a spatial transcriptomics method for imaging gene expression directly in intact tissues (in situ). “With SABER-FISH, we still were orders of magnitude away from capturing cells’ complete gene expression programs, with many thousands of different RNA molecules per cell. RNA molecules are just too densely packed to be captured in their entirety using present imaging techniques,” said co-first and co-corresponding author Kishi. “Light-Seq solves this problem by combining high-resolution barcode labeling with full-transcriptome sequencing via NGS, giving us the best of both worlds and additional key advantages.” At the time of the study, Kishi was a Wyss Technology Development Fellow on Yin’s team, and is now pursuing a path toward commercializing Light-Seq together with some of her co-authors.

“To specifically sequence the cells in custom-selected locations of intact tissue samples, we developed a new approach for photocrosslinking DNA barcodes to copies of RNA molecules, and a DNA nanotechnology-powered procedure that makes them and their attached RNA sequences readable by NGS,” said co-first author Liu, a Postdoctoral Fellow in Yin’s group who previously co-developed a parallelized DNA barcoding platform for a super-resolution imaging method called “Action-PAINT” that also became one of the core components of Light-Seq.

First, DNA primers “base-pair” with RNA molecules in cells, and are extended to create copies of the RNA sequences called complementary DNA sequences (cDNAs). Then, DNA barcode strands containing an ultrafast photocrosslinker nucleotide are in turn base-paired to the cDNAs in the cells. These become permanently linked together when a target cell is lit up under the microscope through a stencil-like optical device that keeps other, non-target cells in the microscopic field in the dark and thus spares them from the photocrosslinking reaction. After washing the barcoded DNA sequences out of cells that were not permanently linked in situ, the procedure can be repeated with different barcodes and light patterns to label more regions of interest.

“To be able to integrate this barcoding workflow with NGS, we engineered a new stitching reaction that is based on DNA nanotechnology. This innovation allows us to convert our barcoded cDNAs into contiguous readout sequences. We can then extract the complete collection of barcode-bearing cDNA sequences from the sample, and analyze them with standard NGS techniques,” explained Saka, one of the study’s corresponding authors who is currently a Group Leader at the European Molecular Biology Laboratory in Heidelberg, Germany. “Ultimately, each barcode traces the full transcriptome readout back to the pre-selected cells in the tissue sample, which remains intact for subsequent analyses. This provides us the unique chance to revisit the exact same cells after sequencing for validation or further exploration.”

Eying complex tissues and rare cells

Following the first validation of Light-Seq in cultured cells, Yin’s team wanted to apply it to a complex tissue and partnered up with the group of Constance Cepko, Ph.D. at HMS. Cepko is one of the study’s corresponding authors and the Bullard Professor of Genetics and Neuroscience in the Blavatnik Institute at HMS, and investigates the development of the retina as a model of the nervous system. Kishi, Saka, and Liu joined forces with West in Cepko’s group to apply Light-Seq to cross-sections of the mouse retina and profile three major layers with different functions. The researchers reached a sequence coverage comparable to single-cell sequencing methods, and found that thousands of RNAs were enriched between the retina’s three major layers. They also showed that after sequence extraction, the tissue samples remained intact and could be further imaged for proteins and other biomolecules.

“Taking Light-Seq to the extreme, we were able to isolate the full transcriptome of a very rare cell type, known as ‘dopaminergic amacrine cells’ (DACs), which is extremely hard to isolate because of its intricate connections to other cells in the retina, by retrieving merely four to eight individually barcoded cells per cross-section,” said West. DACs are involved in regulating the eye’s circadian rhythm by fine-tuning visual perception to different light exposures during the day-night cycle. “Light-Seq also picked up RNAs that were specifically expressed in DACs at low levels, as well as dozens of DAC-specific biomarker RNAs that, to our knowledge, had not been described before, which opens new opportunities to study this rare cell type,” added West, who at the time of the study was a graduate student and then Postdoctoral Fellow with Cepko, and has now joined Kishi in her Light-Seq commercialization effort.

Opening the field of spatial transcriptomics up to NGS also adds information on the level of a single RNA species. “Our sequencing data clearly showed that Light-Seq can determine natural variations in the structure of RNAs. Going forward, we’re very interested in using Light-Seq to better understand the interplay between the immune system, disease-propagating cells, and different therapeutic strategies such as gene and cell therapy,” said Kishi.

“The Light-Seq technology developed in Peng Yin’s group in the Wyss Institute’s Molecular Robotics Initiative yet again shows how pursuing a totally unconventional approach and leveraging synthetic biology can lead to a disruptive technology with great potential for advancing both fundamental research and clinical medicine,” said Wyss Founding Director Donald Ingber, M.D., Ph.D., who is also the Judah Folkman Professor of Vascular Biology at Harvard Medical School and Boston Children’s Hospital, and the Hansjörg Wyss Professor of Bioinspired Engineering at the Harvard John A. Paulson School of Engineering and Applied Sciences.

Other authors of the study are Yin lab members Kuanwei Sheng, Jack Jordanides, and Matthew Serrata. It was funded by the Wyss Institute through its Validation Project Program and a Technology Development Fellowship to Kishi, grants from the Office of Naval Research (grant# N00014-18-1-2549), and National Institutes of Health (grant# 2019-02433), as well as support from the European Molecular Biology Laboratory, and Howard Hughes Medical Institute.