The study was funded by the intramural research grant given to Dr. Ayush Gupta by AIIMS Bhopal. We acknowledge the contribution of laboratory technicians and resident doctors who performed and read the tests diligently during routine and emergency hours.

The study, funded by the intramural research grant given to Dr. Ayush Gupta by AIIMS Bhopal, was approved by the Institutional Human Ethics Committee (IHEC) vide letter no: IHEC- LOP/2022/IL072.
NOTE: A sample volume of 5 ml was used based on studies done by Quesada et al.25 and Munoz-Davila et al.27.
1. Standard inoculum protocol (SIP) for bacterial identification using aMIAST
<ol>
	<li>Wear clean gloves, and inside a Class-IIa biosafety cabinet (BSC), disinfect the septum of +naBC with a swab containing 70% isopropyl alcohol.</li>
	<li>Draw approximately 1 mL of blood-broth mixture using a sterile syringe with a 21 G needle.</li>
	<li>Dispense 1 big drop of the blood-broth mixture from the needle onto the surface of the plated media, namely SBA, CA, and MA. Streak the plates and incubate the culture plates in an incubator at 37 &#176;C &#177; 2 &#176;C under aerobic conditions for 18-24 h.</li>
	<li>After incubation, examine the plates for the appearance of isolated colonies in a BSC and proceed further for identification and AST by aMIAST.</li>
	<li>For each isolate, place an aMIAST polystyrene tube in the aMIAST tube stand and add 3 mL of sterile saline in it using a dispenser attached to the saline bottle.</li>
	<li>Touch three to five morphologically similar colonies with a sterile straight inoculation wire and transfer the bacterial inoculum to the first tube.</li>
	<li>Adjust the turbidity using sterile saline in the inoculated tube between 0.47-0.63 McFarland using a densitometer.</li>
	<li>Place the capillary attachment of the gram-negative aMIAST identification card in the first tube.</li>
	<li>Place the selected cards in an appropriate position on the cassette. The inoculum in the cassette is ready and comes to the aMIAST in filling section. 
	CAUTION: Age of suspension must not exceed 30 min before inoculating the cards.</li>
	<li>Load the cassette into its position in the filler chamber with sample barcode facing inside.</li>
	<li>Close the door and press Fill on the User Interface Screen. Filling is a 70 s cycle. When the cycle is complete the blue indicator light on the system will flash. Placing the cards into the aMIAST system distributes the inoculum within the small chambers of the cards by the machine.</li>
	<li>Remove cassette from filling chamber, close door, and place in loading chamber. Barcodes are automatically scanned and checked against maintain virtual cassette electronic worklist. Straws are automatically sealed, and the cards are automatically loaded into the carousel. Flashing blue arrow on the aMIAST indicates loading is finished.</li>
	<li>Remove cassette waste when finished. See waste disposal procedure in product literature or follow other standard practices. Use remainder of suspension in the tubes to subculture on CLED agar for purity check of the isolates.</li>
	<li>Read the results after the instrument completes the analysis.</li>
</ol>
2. Direct inoculum protocol (DIP) for bacterial identification using aMIAST
<ol>
	<li>Wear sterile gloves, and inside a biosafety cabinet, clean the septum of +naBC with a swab containing 70% isopropyl alcohol.</li>
	<li>Using a sterile syringe with a 21 G needle, take 5 mL of aliquot from the blood-broth mixture of +naBC and transfer it to a serum separator tube (SST) after disinfecting the rubber septum with 70% isopropyl alcohol (Figure 2A).</li>
	<li>Centrifuge this aliquot for 10 min at 160 x g to settle the blood cells in the blood-broth mixture. After the first centrifugation, observe the supernatant in which blood cells will settle down.</li>
	<li>Open the cap of the vial inside a biosafety cabinet, and using a sterile tip and pipette, carefully remove the supernatant and transfer it to a new plain blood collection vial (red top) by removing its top.</li>
	<li>Place the cap on the vial and centrifuge it again for 10 min at 2000 x g. After the second centrifugation, a bacterial pellet will form at the bottom.</li>
	<li>Aspirate the supernatant and discard it using a sterile pipette and tip. The bacterial pellet will remain at the bottom of the tube and will be used to inoculate the aMIAST identification card. 
	NOTE: A serum separator tube was used in the first centrifugation at 160 x g. This was based on studies done by Quesada et al.25 and Munoz-Davila et al.27, where the first centrifugation step was done approximately at 30 x g and 60 x g, respectively. The blood-broth mixture from a +aBC was first centrifuged at low speed in an SST to pellet out the blood cells.</li>
	<li>Place an aMIAST polystyrene tube in the aMIAST tube stand and add 3 mL of sterile saline in it using a dispenser attached to the saline bottle.</li>
	<li>Using a sterile inoculation loop, take the bacterial pellet from the bottom of the vial and inoculate it in the aMIAST tube</li>
	<li>Repeat steps 1.7-1.14.</li>
</ol>
3. AST by EUCAST RAST protocol4
<ol>
	<li>Keep uninoculated 90 mm circular Mueller-Hinton agar (MHA) plates ready in the biosafety cabinet.</li>
	<li>Wear sterile gloves, and inside a biosafety cabinet, clean the septum of +naBC with a swab containing 70% isopropyl alcohol.</li>
	<li>Using a sterile syringe, aspirate 125 &#181;L &#177; 25 &#181;L of undiluted blood-broth mixture from +naBC and add to each MHA plate in the center.</li>
	<li>Spread the broth gently over the plates using a sterile cotton swab in three directions and apply &#8804; 6 antimicrobial disks on each plate.</li>
	<li>Incubate the plates in an aerobic incubator at 35 &#176;C&#177; 1 &#176;C for 8 h. After completion of incubation, observe the purity of the isolate.</li>
	<li>Read the inhibition zones at 8 h &#177; 5 min. Interpret results using the RAST breakpoint table for short incubation after checking the bacterial identification results in the aMIAST.</li>
	<li>Report AST results only if the isolate is identified as one of the RR-GN and the MHA and CLED plates are growing a single morphotype.</li>
</ol>
4. Quality control
<ol>
	<li>Perform internal quality control for the SIP protocol of aMIAST as per the manufacturer&#39;s instructions using recommended reference strains.</li>
	<li>Perform internal quality control of the RAST method weekly using the recommended reference strain of E. coli as described below.
	<ol>
		<li>Arrange 4 sterile glass tubes in a tube stand. Dispense 3 mL of sterile saline in the first tube and 990 &#181;L of sterile saline in each of the second, third, and fourth tubes.</li>
		<li>Make a 0.5 McFarland suspension of the QC strain from the isolated colonies of an overnight culture on plated media.</li>
		<li>Using a sterile pipette and tip, transfer 10 &#181;L of suspension from the first tube to the second tube.</li>
		<li>After mixing, transfer 10 &#181;L of suspension from the second to the third tube and then subsequently to the last tube.</li>
		<li>From the last tube, take 1 mL of the inoculum using a sterile syringe with a needle and add it to an uninoculated aBC.</li>
		<li>Simultaneously add 5 mL of sterile sheep blood in the aBC using a sterile syringe with a needle and incubate it in the CBCMS till it flags positive due to change in the color of the liquid emulsion sensor at the base of the aBC.</li>
		<li>Repeat steps as explained in steps 1-3 for identification by SIP, DIP and RAST, respectively. The expected results are that the QC strain should be identified correctly by both identification protocols of the aMIAST and the zone diameters in RAST plates should be within the specified range28.</li>
	</ol>
	</li>
</ol>
5. Statistical analysis
<ol>
	<li>Consider microbial identification using SIP as gold standard and if the same identification is obtained by DIP, consider it as concordant.</li>
	<li>If an RR-GN i.e., one of E. coli, K. pneumoniae, P. aeruginosa, and A. baumannii complex identified using SIP is discordant in the DIP, consider this as Major error (ME) whereas consider the reverse as very major error (VME) as it has the potential of issuing of a report with wrong identification.</li>
	<li>Calculate the concordance rate for RR-GN as the ratio of the total number of concordant RR-GN to the total number of RR-GN identified by SIP multiplied by 100.</li>
	<li>Calculate ME rate as the ratio of number of +naBCs identified as having a non-RR-GN to the total number of +naBCs with RR-GN identified by SIP multiplied by 100.</li>
	<li>Calculate VME rate as the ratio of number of +naBCs misidentified as having an RR-GN in DIP to the total no. of +naBCs tested by DIP multiplied by 100.</li>
	<li>Calculate the time to isolate identification (TTI) as the time taken to identify the isolate by both protocols from the time of blood culture flagging by the CBCMS.</li>
	<li>Calculate the differences between the DIP and SIP as a reduction in the TTI. Calculate this only for the concordant +naBCs having an RR-GN. Note the respective time points from the clocks of CBCMS and aMIAST.</li>
	<li>Manage data and analyze using a spreadsheet. Use the Mann-Whitney U test for continuous variables, considering a two-sided p-value of &#8804; 0.05 as statistically significant.</li>
</ol>

Accelerated Antimicrobial Susceptibility Testing in Blood Culture Bottles

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H., Campa, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+identification+and+antimicrobial+susceptibility+testing+of+Gram-positive+cocci+in+blood+cultures+by+direct+inoculation+into+the+BD+Phoenix+system.">Rapid identification and antimicrobial susceptibility testing of Gram-positive cocci in blood cultures by direct inoculation into the BD Phoenix system.</a> Clin Microbiol Infect. 16 (7), 986-991 (2010).</li><li>Barreales, A., Lara, M., Hern&#225;ndez, I., D&#237;ez, O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+identification+and+susceptibility+testing+of+Gram-positive+cocci+in+BacT/ALERT+blood+cultures+by+direct+inoculation+into+the+Vitek+2+system.">Rapid identification and susceptibility testing of Gram-positive cocci in BacT/ALERT blood cultures by direct inoculation into the Vitek 2 system.</a> Rev Esp Quimioter. 24 (3), 131-135 (2011).</li></ol>

The authors have nothing to disclose.

Using DIP, we successfully identified the RR-GNs with considerable diagnostic accuracy. The mean TTI after positive flagging of aBC was only 507 min (~ 8.5 h). Thus, when done in conjunction with the EUCAST RAST method for AST determination, it can give isolate identification at 8 h AST reading time. This approach has the potential to implement the EUCAST RAST method obviating the need for mass spectrometry-based identification. This is a boon for the low-resource settings who wish to implement the EUCAST RAST method in ...

Sepsis, an important global health problem, is defined as life-threatening organ dysfunction due to a dysregulated host response to infection. The Global Burden of Diseases Study estimated that there were 48.9 million cases of sepsis and 11 million sepsis-related deaths worldwide in 2017, which accounted for almost 20% of all global deaths1. Around 2/3rd of bloodstream infections (BSI) causing mortality are due to gram-negative bacterial pathogens2. The leading causes of mortality amongst gram-negatives (GN) are Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii,&#160;which account for around 40% of cases amongst 33 bacterial pathogens2.
Blood cultures remain the gold standard for diagnosing BSI, and rapid microbial identification along with antimicrobial susceptibility testing (AST) results is the key to management. It has been estimated that there is a 9% increase in odds of mortality with each-hour delay in instituting appropriate antimicrobials in sepsis3. The turnaround time (TAT) of microbiologically positive blood culture reports with AST results is around 48-72 h with the available microbiological tools in resource-limited settings, even with automated systems. As a result of this subpar TAT, broad-spectrum antimicrobials are used empirically, contributing to the burgeoning problem of antimicrobial resistance (AMR). Recognizing this dire need to reduce TAT for microbiological culture techniques for sepsis, EUCAST and CLSI are moving towards performing AST directly from positively flagged blood culture bottles (+aBC)4,5.
In 2018, EUCAST first introduced the rapid AST (RAST) method for determining AST by Kirby-Bauer disk diffusion method at short incubation times, i.e., 4 h, 6 h and 8 h, directly from +aBC6,7. The method is presently validated for determining AST for +aBCs containing one of the 8 most common causes of BSI namely E. coli, K. pneumoniae, P. aeruginosa, and A. baumannii complex&#160;amongst gram-negatives and Staphylococcus aureus, Enterococcus faecalis, E. faecium, and Streptococcus pneumoniae amongst gram-positives8.The breakpoints for AST determination at various time intervals are provided as per microbial species listed above. Hence, before categorical interpretation of AST results, microbial identification is necessary. However, the RAST standard does not specify the method to enable microbial identification within this time frame.
The majority of studies evaluating the EUCAST RAST method in their setting have used mass spectrometry-based microbial identification after short incubation on plated media to identify micro-organisms9,10,11,12,13,14,15,16,17. However, mass spectrometry instruments are not widely available, especially in low to middle-income countries (LMICs), which greatly limits the potential usefulness of this method. Few studies have reported implementation of this method in their centers without using mass spectrometry18,19,20. Tay&#351;i et al.18 reported a broad categorization of GN amongst Enterobacterales, Pseudomonas, and Acinetobacter spp. based on gram stain morphology and oxidase test before interpreting AST results. In other studies from this center, by Gupta et al.19 and Siddiqui et al.20, species-level microbial identification was done by preparing a bacterial pellet from the positively flagged blood-broth mixture and inoculating it on the conventional biochemical tests. While Tay&#351;i et al.18 did not comment upon the accuracy of microbial identification with their approach, Gupta et al.19 reported that with their approach in 165/176 (94%) cases, a RAST reportable gram-negative (RR-GN), i.e., either of E. coli, K. pneumoniae, P. aeruginosa, and A. baumannii complex. However, with the latter approach, the reading of RAST results was done retrospectively using 8 h zone diameter breakpoints only after the full incubation of conventional biochemical results i.e., 18-24 h post-inoculation, and the average time for reporting was around 2 days.
To reduce the TAT of clinical reports further, we propose an alternative methodology to enable early identification of GN present in +aBCs using aMIAST. Before the introduction of mass spectrometry-based microbial identification systems, these automated identification systems were considered the standard of care for microbial identification, where identification was enabled by colorimetric and/or fluorometric changes induced by test bacteria when inoculated in miniaturized biochemical tests harbored in a cassette and matching the results with their isolate database. The average time to identification in these systems is around 4 h to 8 h however, they are limited by the fact that the manufacturers recommend overnight growth of microbes before their respective identification cards can be inoculated. This requirement greatly limits their usefulness in reducing the time to report.
Few studies have evaluated methods to directly identify microbes from +aBCs using these automated systems21,22,23,24,25,26,27. In the case of +aBCs containing monomorphic GN, the majority of studies showed excellent concordance between direct inoculation from bacterial pellet made from positive blood-broth mixture and standard colony incubation. However, in the case of gram-positives, the concordance rates were suboptimal. As the average time to positivity of +aBCs is between 8 h and 16 h and identification of GN takes ~4 h to 8 h in an automated microbial identification system, we hypothesize that by employing direct inoculation protocol in the automated microbial identification, we can complete the clinical reporting of +aBCs with GN having a RR-GN within 24 h of sample receiving.
Setting for the study 
The present study was conducted in the clinical bacteriology laboratory of a 950-bed, academic, tertiary care institute of national importance (INI) in Central India from January to October 2023. The laboratory is equipped with a continuous blood culture monitoring system (CBCMS) and aMIAST. The bacteriology laboratory is functional round-the-clock with the availability of technicians and microbiologists for processing and reporting any positively flagged blood culture bottle (+aBCs).
Microbial methods used here 
The workflow of the study is shown in Figure 1. The +aBCs showing monomorphic GNs (+naBC) were processed by direct inoculation of corresponding identification cards to enable identification and AST using EUCAST RAST protocol. These results were compared with the standard-of-care (SoC) method for +aBCs i.e., subculturing on conventional plated media through sheep blood agar (SBA), chocolate agar (CA), and MacConkey agar (MA), incubated aerobically for 16 h to 24 h followed by identification and AST cards given by aMIAST when isolated colonies appear. Blood cultures showing gram-positive cocci, gram-positive bacilli, budding yeast cells, and &#8805;2 different micro-organisms on initial gram staining or plated media were excluded from the study.

<table><tbody><tr><td>&lt;strong&gt;ANTIMICROBIAL DISKS&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Amikacin disk 30 &amp;micro;g</td><td>Himedia, Mumbai, India</td><td>SD035-1VL</td><td>Antimicrobial susceptibility testing&amp;nbsp;</td></tr><tr><td>Amoxyclav disk (20/10 &amp;micro;g)</td><td>Himedia, Mumbai, India</td><td>SD063-1VL</td><td>Antimicrobial susceptibility testing&amp;nbsp;</td></tr><tr><td>Cefotaxime disk 5 &amp;micro;g</td><td>Himedia, Mumbai, India</td><td>SD295E-1VL</td><td>Antimicrobial susceptibility testing&amp;nbsp;</td></tr><tr><td>Ceftazidime disk 10 &amp;micro;g</td><td>Himedia, Mumbai, India</td><td>SD062A-1VL</td><td>Antimicrobial susceptibility testing&amp;nbsp;</td></tr><tr><td>Ciprofloxacin disk (5 &amp;micro;g)</td><td>Himedia, Mumbai, India</td><td>SD060-1VL</td><td>Antimicrobial susceptibility testing&amp;nbsp;</td></tr><tr><td>Co-Trimoxazole disk (23.75/1.25 &amp;micro;g)</td><td>Himedia, Mumbai, India</td><td>SD010-1VL</td><td>Antimicrobial susceptibility testing&amp;nbsp;</td></tr><tr><td>Gentamicin disk 10 &amp;micro;g</td><td>Himedia, Mumbai, India</td><td>SD016-1VL</td><td>Antimicrobial susceptibility testing&amp;nbsp;</td></tr><tr><td>Imipenem disk 10 &amp;micro;g</td><td>Himedia, Mumbai, India</td><td>SD073-1VL</td><td>Antimicrobial susceptibility testing&amp;nbsp;</td></tr><tr><td>Levofloxacin disk 5 &amp;micro;g</td><td>Himedia, Mumbai, India</td><td>SD216-1VL</td><td>Antimicrobial susceptibility testing&amp;nbsp;</td></tr><tr><td>Meropenem disk 10 &amp;micro;g&amp;nbsp;</td><td>Himedia, Mumbai, India</td><td>SD727-1VL</td><td>Antimicrobial susceptibility testing&amp;nbsp;</td></tr><tr><td>Piperacillin-tazobactam disk (30/6 &amp;micro;g)</td><td>Himedia, Mumbai, India</td><td>SD292E-1VL</td><td>Antimicrobial susceptibility testing&amp;nbsp;</td></tr><tr><td>Tobramycin disk 10 &amp;micro;g</td><td>Himedia, Mumbai, India</td><td>SD044-1VL</td><td>Antimicrobial susceptibility testing&amp;nbsp;</td></tr><tr><td>ATCC &lt;em&gt;Escherichia coli &lt;/em&gt;25922</td><td>Microbiologics, Minnesota USA</td><td>0335A</td><td>Recommended Gram negative bacterial strain for quality control in RAST</td></tr><tr><td>BacT-Alert 3D 480</td><td>bioMerieux, Marcy d&amp;rsquo; Etoille, France</td><td>412CM8423</td><td>Continuous automated blood culture system</td></tr><tr><td>Biosafety cabinet II Type A2</td><td>Dyna Filters Pvt. Limited, Pune, India</td><td>DFP-2/21-22/149</td><td>For protection against hazardous&amp;nbsp; and infectious agents and to maintain quality control</td></tr><tr><td>Blood agar base no. 2</td><td>Himedia, Mumbai, India</td><td>M834-500G</td><td>Preparation of blood agar and chocolate agar</td></tr><tr><td>Clinical Centrifuge Model SP-8BL</td><td>Laby Instruments, Ambala, India</td><td>HLL/2021-22/021</td><td>Centrifugation at low and high speed for separation of supernatant</td></tr><tr><td>Dispensette S Analog-adjustable bottle-top dispenser&amp;nbsp;</td><td>BrandTech, Essex CT, England</td><td>V1200</td><td>Dispensing accurate amount of saline</td></tr><tr><td>MacConkey agar&amp;nbsp;</td><td>Himedia, Mumbai, India</td><td>M008-500G</td><td>Differential media for Lactose fermenters/ non-fermenters Gram negative bacilli</td></tr><tr><td>Micropipette (100-1000 &amp;micro;L)</td><td>Axiflow Biotech Private Limited, Delhi, India</td><td>NJ478162</td><td>Transferring supernatant after first centrifugation, discarding supernatant after second centrifugation</td></tr><tr><td>Micropipette tips (200-1000 &amp;micro;L)</td><td>&amp;lrm;Tarsons Products Pvt. Ltd., Kolkata, India</td><td>521020</td><td>Transferring supernatant after first centrifugation, discarding supernatant after second centrifugation</td></tr><tr><td>Mueller-Hinton agar&amp;nbsp;</td><td>Himedia, Mumbai, India</td><td>M173-500G</td><td>Antimicrobial susceptibility testing by Kirby-Bauer method of disk diffusion</td></tr><tr><td>Nichrome loop D-4</td><td>Himedia, Mumbai, India</td><td>LA019</td><td>For streaking onto culture media</td></tr><tr><td>Nichrome straight wire</td><td>Himedia, Mumbai, India</td><td>LA022</td><td>For stab inoculation</td></tr><tr><td>Nulife sterile Gloves</td><td>MRK healthcare Pvt Limited, Mumbai, India</td><td></td><td>For safety precautions</td></tr><tr><td>Plain vial (Vial with red top), Advance BD vacutainer</td><td>Becton-Dickinson, Cockeysville, MD, USA</td><td>367815</td><td>Obtaining pellet after second centrifugation</td></tr><tr><td>Sheep blood</td><td>Labline Trading Co., Hyderabad, India</td><td>70014</td><td>Preparation of blood agar and chocolate agar</td></tr><tr><td>SST II tube, Advance BD vacutainer</td><td>Becton-Dickinson, Cockeysville, MD, USA</td><td>367954</td><td>Supernatant separation in first centrifugation</td></tr><tr><td>Sterile cotton swab (w/Wooden stick)</td><td>Himedia, Mumbai, India</td><td>PW005-1X500NO</td><td>Lawn culture of blood culture broth for antimicrobial susceptibility testing</td></tr><tr><td>Sterile single use hypodermic syringe 5ml/cc</td><td>Nihal Healthcare, Solan, India</td><td>2213805NB2</td><td>Preparing aliquots from +aBC</td></tr><tr><td>VITEK DensiCHEK McFarland reference kit</td><td>bioMerieux, Marcy d&amp;rsquo; Etoille, France</td><td>422219</td><td>Densitometer to check the turbidity of suspension</td></tr><tr><td>VITEK saline solution (0.45% NaCl)</td><td>bioMerieux, Marcy d&amp;rsquo; Etoille, France</td><td>V1204</td><td>Adjustment of McFarland Standard turbidity</td></tr><tr><td>VITEK tube stand&amp;nbsp;</td><td>bioMerieux, Marcy d&amp;rsquo; Etoille, France</td><td>533306-4 REV</td><td>Stand for proper placement of tubes before ID card inoculation</td></tr><tr><td>VITEK tubes</td><td>bioMerieux, Marcy d&amp;rsquo; Etoille, France</td><td></td><td>Tubes for inoculum preparation</td></tr><tr><td>VITEK-2 Compact 60</td><td>bioMerieux, Marcy d&amp;rsquo; Etoille, France</td><td>VKC15144</td><td>Automated identification and AST system</td></tr><tr><td>VITEK-2 GN card</td><td>bioMerieux, Marcy d&amp;rsquo; Etoille, France</td><td>21341</td><td>Identification of Gram negative bacilli</td></tr></tbody></table>

direct microbial identification using an automated microbial identification system to facilitate the eucast rast method without mass spectrometry

Gram-negative (GN) sepsis is a medical emergency where management in resource-limited settings relies on conventional microbiological culture techniques providing results in 3-4 days. Recognizing this delay in turnaround time (TAT), both EUCAST and CLSI have developed protocols for determining AST results directly from positively flagged automated blood culture bottles (+aBCs). EUCAST rapid AST (RAST) protocol was first introduced in 2018, where zone diameter breakpoints for four common etiological agents of GN sepsis, i.e., Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii complex can be reported. However, those clinical laboratories that have implemented this method in their routine workflow rely on mass spectrometry-based microbial identification, which is not easily available, thus precluding its implementation in resource-limited settings. To circumvent it, we evaluated a direct inoculum protocol (DIP) using a commercial automated microbial identification and antimicrobial susceptibility testing system (aMIAST) to enable early microbial identification within 8 h of positive flagging of aBC. We evaluated this protocol from January to October 2023 to identify the four RAST reportable GN (RR-GN) in the positively flagged aBC. The microbial identification results in DIP were compared with the standard inoculum preparation protocol (SIP) in aMIAST. Of 204 +aBCs with monomorphic GN (+naBC), one of the 4 RR-GN was identified in 105 +naBCs by SIP (E. coli: 50, K. pneumoniae: 20, P. aeruginosa: 9 and A. baumannii complex: 26). Of these, 94% (98/105) were correctly identified by DIP whereas major error and very major error rates were 6% (7/105) and 1.7% (4/240), respectively. When DIP for microbial identification is done using the EUCAST RAST method, provisional clinical reports can be provided within 24 h of receiving the sample. This approach has the potential to significantly reduce the TAT, enabling early institution of appropriate antimicrobial therapy.

General outcomes 
During the study period, 240 +naBCs underwent identification by aMIAST using both DIP and SIP. Of these, 15% (36/240) +naBCs were found to be polymicrobial after overnight incubation on the plated media. Of the 204 +naBCs, the proportion of RR-GN identified by SIP was 51.5% (105/204). Amongst them, 47.6% (50/105) were E. coli, 19% (20/105) K. pneumoniae, 8.6% (9/105) P. aeruginosa and 24.8% (26/105) A. baumannii complex. A detailed description of...

Author Spotlight: Accelerating Diagnostic Accuracy with Direct Identification of Gram-Negatives from Blood Culture Bottles

EUCAST has developed a direct antimicrobial susceptibility testing (AST) protocol for automated blood cultures. However, its dependence on mass spectrometry-based microbial identification can be obviated by using a direct inoculum preparation protocol in an automated microbial identification system. This approach can provide AST reports within 24 h of sample collection.

Direct Microbial Identification using An Automated Microbial Identification System to Facilitate the EUCAST RAST Method Without Mass Spectrometry

Gram-negative (GN) sepsis is a medical emergency where management in resource-limited settings relies on conventional microbiological culture techniques ...

direct-microbial-identification-using-an-automated-microbial

Research

JoVE Journal

Medicine

764 Views.  All India Institute of Medical Sciences, Bhopal. Dit onderzoek heeft tot doel de diagnostische nauwkeurigheid van Gram-negatieven rechtstreeks uit bloedkweekflessen met een positieve vlag te evalueren door middel van een geautomatiseerd microbieel identificatiesysteem. Het doel is om het te gebruiken als een hulpmiddel voor vroege klinische rapportage door middel van de EUCAST-testmethode voor snelle antimicrobiële gevoeligheid. De EUCAST RAST-methode is onlangs in 2018 geïntroduceerd om rapportage van testresultaten voor antimicrobiële ...

Video: Auteur in de schijnwerpers: diagnostische nauwkeurigheid versnellen met directe identificatie van gramnegatieven uit bloedkweekflessen

Rapid High-throughput Species Identification of Botanical Material Using Direct Analysis in Real Time High Resolution Mass Spectrometry

We demonstrate that direct analysis in real time-high resolution mass spectrometry can be used to produce mass spectral profiles of botanical material, and that these chemical fingerprints can be used for plant species identification. The mass spectral data can be acquired rapidly and in a high throughput manner without the need for sample extraction, derivatization or pH adjustment steps. The use of this technique bypasses challenges presented by more conventional techniques including lengthy chromatography analysis times and resource intensive methods. The high throughput capabilities of the direct analysis in real time-high resolution mass spectrometry protocol, coupled with multivariate statistical analysis processing of the data, provide not only class characterization of plants, but also yield species and varietal information. Here, the technique is demonstrated with two psychoactive plant products, Mitragyna speciosa (Kratom) and Datura (Jimsonweed), which were subjected to direct analysis in real time-high resolution mass spectrometry followed by statistical analysis processing of the mass spectral data. The application of these tools in tandem enabled the plant materials to be rapidly identified at the level of variety and species.

A method for species identification of botanical material by direct analysis in real time-high resolution mass spectrometry and multivariate statistical analysis is presented.

We demonstrate that direct analysis in real time-high resolution mass spectrometry can be used to produce mass spectral profiles of botanical material, ...

Chemistry

Identification and Isolation of Slow-Dividing Cells in Human Glioblastoma Using Carboxy Fluorescein Succinimidyl Ester (CFSE)

Tumor heterogeneity represents a fundamental feature supporting tumor robustness and presents a central obstacle to the development of therapeutic strategies1. To overcome the issue of tumor heterogeneity, it is essential to develop assays and tools enabling phenotypic, (epi)genetic and functional identification and characterization of tumor subpopulations that drive specific disease pathologies and represent clinically relevant targets. It is now well established that tumors exhibit distinct sub-fractions of cells with different frequencies of cell division, and that the functional criteria of being slow cycling is positively associated with tumor formation ability in several cancers including those of the brain, breast, skin and pancreas as well as leukemia2-8. The fluorescent dye carboxyfluorescein succinimidyl ester (CFSE) has been used for tracking the division frequency of cells in vitro and in vivo in blood-borne tumors and solid tumors such as glioblastoma2,7,8. The cell-permeant non-fluorescent pro-drug of CFSE is converted by intracellular esterases into a fluorescent compound, which is retained within cells by covalently binding to proteins through reaction of its succinimidyl moiety with intracellular amine groups to form stable amide bonds9. The fluorescent dye is equally distributed between daughter cells upon divisions, leading to the halving of the fluorescence intensity with every cell division. This enables tracking of cell cycle frequency up to eight to ten rounds of division10. CFSE retention capacity was used with brain tumor cells to identify and isolate a slow cycling subpopulation (top 5% dye-retaining cells) demonstrated to be enriched in cancer stem cell activity2. 
This protocol describes the technique of staining cells with CFSE and the isolation of individual populations within a culture of human glioblastoma (GBM)-derived cells possessing differing division rates using flow cytometry2. The technique has served to identify and isolate a brain tumor slow-cycling population of cells by virtue of their ability to retain the CFSE labeling.

Identification and Isolation of Slow-Dividing Cells in Human Glioblastoma Using Carboxy Fluorescein Succinimidyl Ester CFSE

This video protocol demonstrates the application of the fluorescent dye carboxyfluorescein succinimidyl ester (CFSE) for the identification and separation of different sub-populations of cells in human glioblastoma based on frequency of cell division.

Tumor heterogeneity represents a fundamental feature supporting tumor robustness and presents a central obstacle to the development of therapeutic ...

Identification of Sleeping Beauty Transposon Insertions in Solid Tumors using Linker-mediated PCR

Genomic, proteomic, transcriptomic, and epigenomic analyses of human tumors indicate that there are thousands of anomalies within each cancer genome compared to matched normal tissue. Based on these analyses it is evident that there are many undiscovered genetic drivers of cancer1. Unfortunately these drivers are hidden within a much larger number of passenger anomalies in the genome that do not directly contribute to tumor formation. Another aspect of the cancer genome is that there is considerable genetic heterogeneity within similar tumor types. Each tumor can harbor different mutations that provide a selective advantage for tumor formation2. Performing an unbiased forward genetic screen in mice provides the tools to generate tumors and analyze their genetic composition, while reducing the background of passenger mutations. The Sleeping Beauty (SB) transposon system is one such method3. The SB system utilizes mobile vectors (transposons) that can be inserted throughout the genome by the transposase enzyme. Mutations are limited to a specific cell type through the use of a conditional transposase allele that is activated by Cre Recombinase. Many mouse lines exist that express Cre Recombinase in specific tissues. By crossing one of these lines to the conditional transposase allele (e.g. Lox-stop-Lox-SB11), the SB system is activated only in cells that express Cre Recombinase. The Cre Recombinase will excise a stop cassette that blocks expression of the transposase allele, thereby activating transposon mutagenesis within the designated cell type. An SB screen is initiated by breeding three strains of transgenic mice so that the experimental mice carry a conditional transposase allele, a concatamer of transposons, and a tissue-specific Cre Recombinase allele. These mice are allowed to age until tumors form and they become moribund. The mice are then necropsied and genomic DNA is isolated from the tumors. Next, the genomic DNA is subjected to linker-mediated-PCR (LM-PCR) that results in amplification of genomic loci containing an SB transposon. LM-PCR performed on a single tumor will result in hundreds of distinct amplicons representing the hundreds of genomic loci containing transposon insertions in a single tumor4. The transposon insertions in all tumors are analyzed and common insertion sites (CISs) are identified using an appropriate statistical method5. Genes within the CIS are highly likely to be oncogenes or tumor suppressor genes, and are considered candidate cancer genes. The advantages of using the SB system to identify candidate cancer genes are: 1) the transposon can easily be located in the genome because its sequence is known, 2) transposition can be directed to almost any cell type and 3) the transposon is capable of introducing both gain- and loss-of-function mutations6. The following protocol describes how to devise and execute a forward genetic screen using the SB transposon system to identify candidate cancer genes (Figure 1).

Identification of Sleeping Beauty Transposon Insertions in Solid Tumors using Linker-mediated PCR

A method of identifying unknown drivers of carcinogenesis using an unbiased approach is described. The method uses the Sleeping Beauty transposon as a random mutagen directed to specific tissues. Genomic mapping of transposon insertions that drive tumor formation identifies novel oncogenes and tumor suppressor genes

Genomic, proteomic, transcriptomic, and epigenomic analyses of human tumors indicate that there are thousands of anomalies within each cancer genome ...

Endotracheal Intubation in Mice via Direct Laryngoscopy Using an Otoscope

Mice, both wildtype and transgenic, are the principal mammalian model in biomedical research currently. Intubation and mechanical ventilation are necessary for whole animal experiments that require surgery under deep anesthesia or measurements of lung function. Tracheostomy has been the standard for intubating the airway in these mice to allow mechanical ventilation. Orotracheal intubation has been reported but has not been successfully used in many studies because of the substantial technical difficulty or a requirement for highly specialized and expensive equipment. Here we report a technique of direct laryngoscopy using an otoscope fitted with a 2.0 mm speculum and using a 20 G&#160;intravenous catheter as an endotracheal tube. We have used this technique extensively and reliably to intubate and conduct accurate assessments of lung function in mice. This technique has proven safe, with essentially no animal loss in experienced hands. Moreover, this technique can be used for repeated studies of mice in chronic models.

Endotracheal Intubation in Mice via Direct Laryngoscopy Using an Otoscope

We have developed a simple, reliable, and relatively inexpensive method for endotracheal intubation in mice via direct laryngoscopy using an otoscope with a 2.0 mm speculum. This technique is atraumatic and can be used for repeated measurements in chronic experiments. We find it superior to tracheostomy or previously reported nonsurgical techniques.

Mice, both wildtype and transgenic, are the principal mammalian model in biomedical research currently. Intubation and mechanical ventilation are ...

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.

Multivariate techniques including principal component analysis (PCA) have been used to identify signature patterns of regional change in functional brain images. We have developed an algorithm to identify reproducible network biomarkers for the diagnosis of neurodegenerative disorders, assessment of disease progression, and objective evaluation of treatment effects in patient populations.

The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain ...

Rapid Identification of Gram Negative Bacteria from Blood Culture Broth Using MALDI-TOF Mass Spectrometry

An important role of the clinical microbiology laboratory is to provide rapid identification of bacteria causing bloodstream infection. Traditional identification requires the sub-culture of signaled blood culture broth with identification available only after colonies on solid agar have matured. MALDI-TOF MS is a reliable, rapid method for identification of the majority of clinically relevant bacteria when applied to colonies on solid media. The application of MALDI-TOF MS directly to blood culture broth is an attractive approach as it has potential to accelerate species identification of bacteria and improve clinical management. However, an important problem to overcome is the pre-analysis removal of interfering resins, proteins and hemoglobin&#160;contained in blood culture specimens which, if not removed, interfere with the MS spectra and can result in insufficient or low discrimination identification scores. In addition it is necessary to concentrate bacteria to develop spectra of sufficient quality. The presented method describes the concentration, purification, and extraction of Gram negative bacteria allowing for the early identification of bacteria from a signaled blood culture broth.

The application of matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) mass spectrometry (MS) directly to blood culture broth expedites the identification of bacteria. The presented method is a rapid and reliable method for identification of Gram negative bacteria directly from blood culture broth.

An important role of the clinical microbiology laboratory is to provide rapid identification of bacteria causing bloodstream infection. Traditional ...

Immunology and Infection

Preparation of a Blood Culture Pellet for Rapid Bacterial Identification and Antibiotic Susceptibility Testing

Bloodstream infections and sepsis are a major cause of morbidity and mortality. The successful outcome of patients suffering from bacteremia depends on a rapid identification of the infectious agent to guide optimal antibiotic treatment. The analysis of Gram stains from positive blood culture can be rapidly conducted and already significantly impact the antibiotic regimen. However, the accurate identification of the infectious agent is still required to establish the optimal targeted treatment. We present here a simple and fast bacterial pellet preparation from a positive blood culture that can be used as a sample for several essential downstream applications such as identification by MALDI-TOF MS, antibiotic susceptibility testing (AST) by disc diffusion assay or automated AST systems and by automated PCR-based diagnostic testing. The performance of these different identification and AST systems applied directly on the blood culture bacterial pellets is very similar to the performance normally obtained from isolated colonies grown on agar plates. Compared to conventional approaches, the rapid acquisition of a bacterial pellet significantly reduces the time to report both identification and AST. Thus, following blood culture positivity, identification by MALDI-TOF can be reported within less than 1 hr whereas results of AST by automated AST systems or disc diffusion assays within 8 to 18 hr, respectively. Similarly, the results of a rapid PCR-based assay can be communicated to the clinicians less than 2 hr following the report of a bacteremia. Together, these results demonstrate that the rapid preparation of a blood culture bacterial pellet has a significant impact on the identification and AST turnaround time and thus on the successful outcome of patients suffering from bloodstream infections.

A rapid bacterial pellet preparation from a positive blood culture can be used as a sample for applications such as identification by MALDI-TOF, Gram staining, antibiotic susceptibility testing and PCR-based test. The results can be rapidly communicated to clinicians to improve the outcome of patients suffering from bloodstream infections.

Bloodstream infections and sepsis are a major cause of morbidity and mortality. The successful outcome of patients suffering from bacteremia depends on a ...

Identification of Rare Bacterial Pathogens by 16S rRNA Gene Sequencing and MALDI-TOF MS

There are a number of rare and, therefore, insufficiently described bacterial pathogens which are reported to cause severe infections especially in immunocompromised patients. In most cases only few data, mostly published as case reports, are available which investigate the role of such pathogens as an infectious agent. Therefore, in order to clarify the pathogenic character of such microorganisms, it is necessary to conduct epidemiologic studies which include large numbers of these bacteria. The methods used in such a surveillance study have to meet the following criteria: the identification of the strains has to be accurate according to the valid nomenclature, they should be easy to handle (robustness), economical in routine diagnostics and they have to generate comparable results among different laboratories. Generally, there are three strategies for identifying bacterial strains in a routine setting: 1) phenotypic identification characterizing the biochemical and metabolic properties of the bacteria, 2) molecular techniques such as 16S rRNA gene sequencing and 3) mass spectrometry as a novel proteome based approach. Since mass spectrometry and molecular approaches are the most promising tools for identifying a large variety of bacterial species, these two methods are described. Advances, limitations and potential problems when using these techniques are discussed.

Matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) and molecular techniques (16S rRNA gene sequencing) permit the identification of rare bacterial pathogens in routine diagnostics. The goal of this protocol lies in the combination of both techniques which leads to more accurate and reliable data.

There are a number of rare and, therefore, insufficiently described bacterial pathogens which are reported to cause severe infections especially in ...

Use of MALDI-TOF Mass Spectrometry and a Custom Database to Characterize Bacteria Indigenous to a Unique Cave Environment (Kartchner Caverns, AZ, USA)

MALDI-TOF mass spectrometry has been shown to be a rapid and reliable tool for identification of bacteria at the genus and species, and in some cases, strain levels. Commercially available and open source software tools have been developed to facilitate identification; however, no universal/standardized data analysis pipeline has been described in the literature. Here, we provide a comprehensive and detailed demonstration of bacterial identification procedures using a MALDI-TOF mass spectrometer. Mass spectra were collected from 15 diverse bacteria isolated from Kartchner Caverns, AZ, USA, and identified by 16S rDNA sequencing. Databases were constructed in BioNumerics 7.1. Follow-up analyses of mass spectra were performed, including cluster analyses, peak matching, and statistical analyses. Identification was performed using blind-coded samples randomly selected from these 15 bacteria. Two identification methods are presented: similarity coefficient-based and biomarker-based methods. Results show that both identification methods can identify the bacteria to the species level.

Use of MALDI-TOF Mass Spectrometry and a Custom Database to Characterize Bacteria Indigenous to a Unique Cave Environment Kartchner Caverns, AZ, USA

This work details procedures for rapid identification of bacteria using MALDI-TOF MS. The identification procedures include spectrum acquisition, database construction, and follow up analyses. Two identification methods, similarity coefficient-based and biomarker-based methods, are presented.

MALDI-TOF mass spectrometry has been shown to be a rapid and reliable tool for identification of bacteria at the genus and species, and in some cases, ...

Biology

Rapid Antimicrobial Susceptibility Testing by Stimulated Raman Scattering Imaging of Deuterium Incorporation in a Single Bacterium

To slow and prevent the spread of antimicrobial resistant infections, rapid antimicrobial susceptibility testing (AST) is in urgent need to &#65279;quantitatively determine the &#65279;antimicrobial effects on pathogens. &#65279;It typically takes days to complete the AST by conventional methods based on the long-time culture, and they do not work directly for clinical samples. Here, we report a rapid AST &#65279;method enabled by stimulated Raman scattering (SRS) imaging of deuterium oxide (D2O) metabolic incorporation. Metabolic incorporation of D2O into biomass and the metabolic activity inhibition upon exposure to antibiotics at the single bacterium level are monitored by SRS imaging. The&#65279; single-cell metabolism inactivation concentration (SC-MIC) of bacteria upon exposure to antibiotics can be obtained after a total of 2.5 h of sample preparation and detection. Furthermore, this rapid AST method is directly applicable to bacterial samples in complex biological environments, such as urine or whole blood. SRS metabolic imaging of deuterium incorporation is transformative for rapid single-cell phenotypic AST in the clinic.

This protocol presents rapid antimicrobial susceptibility testing (AST) assay within 2.5 h by single-cell-stimulated Raman scattering imaging of D2O metabolism. This method applies to bacteria in the urine or whole blood environment, which is transformative for rapid single-cell phenotypic AST in the clinic.

Direct Microbial Identification using An Automated Microbial Identification System to Facilitate the EUCAST RAST Method Without Mass Spectrometry

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