The problem arises because the most widely used rapid sample preparation method, the commercially available MBT Sepsityper kit, was designed for a task that does not require living bacteria. The kit uses a proprietary lysis buffer, thought to contain ionic detergents such as sodium dodecyl sulphate, to rupture red blood cells, followed by high-speed centrifugation at around 16,000 times gravity to pellet the bacteria and discard cellular debris. The resulting organisms are fed into matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry, which identifies pathogens from their protein and lipid fingerprints. For that purpose, viability is irrelevant. But the new generation of rapid phenotypic antimicrobial susceptibility tests, which promise results within two to three hours, depends entirely on bacteria that are actively dividing the moment they emerge from the extraction process.

This distinction matters most for Gram-positive pathogens. Organisms such as Staphylococcus aureus, which together with other Gram-positive bacteria account for more than half of bloodstream infections, possess a thick cell wall and membrane architecture that renders them far more vulnerable to detergent damage than their Gram-negative counterparts such as Escherichia coli. Previous studies have already hinted at the problem, reporting lower identification scores for Gram-positive organisms processed with Sepsityper. The Southampton group, led by Hywel Morgan and Daniel Spencer, set out to quantify exactly how much harm five different blood lysis protocols inflict on bacterial viability during the earliest stages of growth, the window that rapid susceptibility assays cannot afford to lose.

The researchers spiked healthy human blood with laboratory strains of E. coli and S. aureus, incubated the mixtures in standard aerobic blood culture bottles until they flagged positive, and then processed each bottle with one of five extraction chemistries: the Sepsityper kit, saponin alone, an ammonium chloride and potassium bicarbonate buffer, deionised water lysis by hypoosmotic shock, and a combination of saponin with the non-ionic detergent Triton X-100 supplemented with reducing agents to suppress reactive oxygen species. Each protocol lyses red blood cells by a different mechanism, from detergent-mediated membrane permeabilisation to osmotic swelling, and each carries its own trade-off between how completely the blood cells are destroyed and how gently the bacteria are treated.

To judge the outcome, the team turned to microfluidic impedance cytometry, a label-free technique that measures the electrical properties of thousands of individual cells as they stream through a microchannel lined with microelectrodes. An alternating voltage is applied at two frequencies, 5 MHz and 40 MHz. At the lower frequency the signal reflects cell volume, while at the higher frequency it is sensitive to the cell membrane and wall. Because the channel is only about 20 by 40 micrometres, bacteria can be counted and characterised one by one, even in the presence of residual red cell ghosts and debris, provided their electrical signatures do not overlap. The technique has already been shown to detect antibiotic-induced changes in bacterial impedance within two hours, forming the basis of a rapid susceptibility method known as iFAST.

The impedance data revealed striking differences between the extraction protocols. For E. coli, which reaches very high concentrations in blood culture bottles, all five methods yielded counts in agreement with conventional colony counting, and the bacteria resumed normal growth after only a brief 30-minute lag. For S. aureus, which grows more slowly and is present at roughly tenfold lower concentrations at the time the bottle flags positive, the picture changed dramatically. Samples treated with Sepsityper produced far fewer detectable organisms immediately after extraction, and the population did not begin to grow until two and a half hours had passed. Untreated and saponin-treated samples, by contrast, showed only a one-hour delay before entering exponential growth, with doubling times of around 65 to 67 minutes that were statistically indistinguishable from each other.

Independent confirmation came from optical flow cytometry using live/dead fluorescent staining. The team labelled bacteria with SYTO 9, a green dye that enters all cells, and propidium iodide, a red dye that penetrates only cells with damaged membranes. Immediately after Sepsityper extraction, most S. aureus cells showed strong propidium iodide signal, indicating compromised membranes, while saponin-treated cells looked essentially identical to untreated controls and recovered as quickly. The likely culprit is the ionic detergent in the Sepsityper buffer, which can permeabilise bacterial membranes and may also provoke oxidative stress. Colony imaging after overnight incubation reinforced the finding: S. aureus colonies isolated with Sepsityper were significantly smaller than those from untreated samples, whereas saponin-treated colonies showed no significant difference.

Extraction efficiency told a similar story. Measured against colony counts from untreated cultures, viable E. coli recovery ranged from 37 to 54 percent across the protocols, while S. aureus recovery ranged from just 5 to 35 percent. Saponin delivered the highest impedance-based efficiency for S. aureus at 35 percent and produced the cleanest samples, with debris particles small enough to be separated from the bacteria electrically. The ammonium chloride protocol generated so much debris overlapping with the S. aureus population that accurate counting became impossible, and deionised water lysis performed worst of all, possibly because S. aureus cells adhered to red blood cells and sedimented away with them during centrifugation. For E. coli, the data even suggested that lysis and centrifugation may be unnecessary, since fast-growing Gram-negative organisms can be discriminated from blood cells directly.

Beyond viability, the study highlights a subtler advantage of impedance cytometry for the diagnostic workflow itself. Preparing the inoculum for a phenotypic susceptibility test normally relies on turbidity matching against a McFarland standard, but blood cells and debris inflate turbidity and skew the measurement. Because impedance cytometry counts each bacterium as a discrete electrical event and can distinguish bacteria from red cells, ghosts and platelets by their size and high-frequency phase, it offers a direct route to accurate inoculum preparation at the concentration recommended by EUCAST guidelines. The technique can even discriminate E. coli from S. aureus by their electrical phase, an analogue of conventional Gram staining performed without any reagents or stains.

The implications reach well beyond the laboratory bench. Any rapid susceptibility platform that promises answers within three hours of a blood bottle flagging positive will be defeated if its sample preparation quietly kills or stuns a large fraction of the pathogens, and the organisms most likely to be harmed are precisely the Gram-positive bacteria that dominate bloodstream infections. The Southampton results point to saponin, a mild natural detergent, as the chemistry of choice for preserving viable organisms, and the team now plans to integrate on-chip lysis, automated washing and size-based separation into a streamlined microfluidic sample preparation system. Clinical samples, polymicrobial cultures and a broader panel of Gram-positive pathogens remain the next hurdles, but the study makes clear that the road to same-hour antibiotic decisions runs through gentler chemistry.

Subject of Research: Rapid isolation of viable bacteria from positive blood cultures using microfluidic impedance cytometry to compare blood lysis protocols for antimicrobial susceptibility testing

Article Title: Isolating viable bacteria from positive blood cultures: impedance cytometry analysis

Article References: Isolating viable bacteria from positive blood cultures: impedance cytometry analysis. (n.d.). https://doi.org/10.1007/s10544-026-00847-5

Image Credits: AI Generated

DOI: 10.1007/s10544-026-00847-5

Keywords: bloodstream infections, sepsis, antimicrobial susceptibility testing, impedance cytometry, microfluidics, Sepsityper, saponin, Staphylococcus aureus, Escherichia coli, bacterial viability, MALDI-TOF, antimicrobial resistance

TB-Profiler was developed to profile M. tuberculosis directly from next-generation sequencing data. Rather than waiting days or weeks for laboratory cultures to grow, the tool scans raw sequencing reads for known resistance-conferring mutations and assigns the isolate to one of the major phylogenetic lineages of the tuberculosis bacillus. This approach, known as genotypic antimicrobial susceptibility prediction, has become increasingly important as sequencing costs fall and national tuberculosis programmes adopt whole-genome sequencing for routine diagnostics. The original version of the tool covered 16 anti-TB drugs; the updated release adds delamanid and pretomanid, two newer agents that are central to modern regimens for multidrug-resistant and extensively drug-resistant disease.

The technical heart of the upgrade lies in its expanded and refined mutation libraries. TB-Profiler does not attempt to predict resistance from first principles; instead, it relies on carefully curated catalogues of mutations that have been experimentally or epidemiologically linked to reduced drug susceptibility. The updated version incorporates interpretation rules endorsed by the World Health Organization, ensuring that the tool’s output aligns with internationally recognised standards for reporting resistance to drugs such as bedaquiline and clofazimine, cycloserine and terizidone, and para-aminosalicylic acid. The developers have also added curated loss-of-function mutations, which are changes that disable a gene entirely and are increasingly recognised as important drivers of resistance to newer drug classes.

Why does this matter clinically? Regimens for drug-resistant tuberculosis have changed dramatically in recent years, shifting towards shorter, all-oral combinations built around bedaquiline, pretomanid and linezolid. Choosing the right regimen requires knowing exactly which drugs the infecting strain can tolerate, and phenotypic antimicrobial susceptibility testing, the traditional gold standard, can take weeks because M. tuberculosis grows so slowly. Genotypic prediction from sequencing data can deliver a resistance profile in a fraction of that time, and tools like TB-Profiler make that analysis accessible to laboratories that lack deep bioinformatics expertise, through both a command-line version and a web interface.

The second major pillar of the update is population context. The team has integrated a continuously expanding global genomic database of more than 170,000 isolates, representing all major lineages of the M. tuberculosis complex and spanning 136 countries. This resource allows the tool to place any newly sequenced genome within its global population framework, comparing allele frequencies and identifying how unusual or common a given mutation is across the worldwide diversity of the pathogen. That context is technically important because not every mutation observed in a resistant isolate actually causes resistance; some are simply neutral variants that happen to be common in certain lineages. A global reference panel helps distinguish the two.

Built on top of this database is a new analytical capability for calculating and visualising genomic relatedness between isolates. In tuberculosis surveillance, genomic relatedness is the key to identifying transmission. When two isolates from different patients are nearly identical across their genomes, it strongly suggests that one infected the other, or that both were infected by a common source. By computing distances between genomes and presenting the results in accessible visualisations, the updated TB-Profiler allows public health teams to spot potential transmission chains and outbreaks directly within the same workflow they already use for resistance prediction, rather than juggling separate tools.

To demonstrate the new functionality, the researchers applied it to isolates from Uganda, where they were able to identify potential transmission events among the sampled genomes. The demonstration illustrates the practical value of combining resistance profiling and relatedness analysis in a single platform. In high-burden settings, distinguishing between reactivation of a latent infection picked up years ago and recent active transmission changes the public health response entirely: recent transmission calls for intensified contact tracing and community screening, whereas reactivation points towards the management of latent infection in vulnerable populations.

Accessibility has also been broadened in a way that could prove decisive for global uptake. The updated tool introduces multilingual reporting capabilities, meaning that the clinical reports generated from sequencing data can be delivered in the languages spoken by the health workers who use them. This may sound like a modest feature, but in tuberculosis control it addresses a real barrier: the countries carrying the greatest burden of drug-resistant disease are often those where English is not the primary working language of laboratory and clinical staff. By lowering the language barrier, the developers hope to widen implementation of genomic surveillance in precisely the regions where it is needed most.

The work is a product of an international collaboration spanning the London School of Hygiene and Tropical Medicine, Thailand’s Ministry of Public Health Medical Genetics Center, the South African National Bioinformatics Institute at the University of the Western Cape, Nottingham Trent University and the University of Cambridge. The informatics development was supported by a UKRI EPSRC award in artificial intelligence innovation to accelerate health research, with additional support from the UKRI Medical Research Council. The tool and its associated databases are available in both stand-alone and web-based versions at the team’s hosted platform, and the underlying article is published open access under a Creative Commons licence.

The developers are explicit that this release is a stepping stone rather than a destination. Future versions will leverage the ever-expanding sequencing database to deploy artificial intelligence approaches aimed at refining lineage assignment, improving drug-resistance prediction and sharpening transmission classification, including the identification of resistance-associated mutations that have not yet been characterised. As the global database grows with every sequenced isolate, the statistical power available to such machine-learning methods grows with it, promising a feedback loop in which each new genome makes the tool smarter for the next patient. For a disease that kills well over a million people each year, turning sequencing data into faster treatment decisions and earlier outbreak detection is a goal worth the engineering effort, and the updated TB-Profiler brings that goal measurably closer.

Subject of Research: Genomic prediction of antimicrobial resistance and transmission in Mycobacterium tuberculosis using the updated TB-Profiler tool

Article Title: Updated TB-Profiler: enhanced genotypic antimicrobial resistance prediction and relatedness analysis powered by a database of over 171,000 Mycobacterium tuberculosis genomes

Article References: Phelan, J. E., Sawaengdee, W., Thorpe, J., Thawong, N., Piboonsiri, P., Billows, N., Wang, L., van Heusden, P., Meehan, C., Köser, C. U., Mahasirimongkol, S., Campino, S., & Clark, T. G. (2026). Updated TB-Profiler: enhanced genotypic antimicrobial resistance prediction and relatedness analysis powered by a database of over 171,000 Mycobacterium tuberculosis genomes. Genome Medicine. https://doi.org/10.1186/s13073-026-01767-y

Image Credits: AI Generated

DOI: 10.1186/s13073-026-01767-y

Keywords: tuberculosis, TB-Profiler, drug resistance, whole-genome sequencing, Mycobacterium tuberculosis, antimicrobial susceptibility prediction, genomic surveillance, transmission analysis, WHO mutation catalogue, bedaquiline, pretomanid, public health genomics