Extramedullary myelomas (plasmacytoma) are malignant proliferations of plasma cells in the absence of bone involvement. When they occur in the soft tissue they usually involve the upper respiratory tract and oral cavity. Extramedullary plasmacytomas of breast are uncommon.A 70 year-old woman with bilateral breast masses underwent excisional biopsy for suspected primary carcinoma that subsequently proved to be a recurrence from extramedullary plasmacytoma of the mediastinum. This was diagnosed and treated 5-years prior to appearance of breast lumps.Though uncommon, considering the possibility of metastatic carcinoma and primary, secondary or recurrent lymphoproliferative disease presenting as a breast mass may avoid unnecessary surgeries. Extramedullary myelomas (plasmacytoma) are malignant proliferations of plasma cells in the absence of bone involvement. When occur in the soft tissue, it usually involve the upper respiratory tract and oral cavity . PlasmacThis report describes a patient with bilateral breast masses who underwent excision biopsy for suspected primary carcinoma that subsequently proved to be a recurrence from extramedullary plasmacytoma of mediastinum treated 5 years ago. To the best of our knowledge, this is the first case report of bilateral recurrence of a primary extramedullary plasmacytoma in breast tissues after a long disease-free interval.A 70 year-old woman with a one-month history of bilateral breast masses was referred to our cancer center for surgical evaluation. There was no associated breast pain, skin change or nipple discharge. There was no history of bone pain, weight loss, fatigue, fever or other systemic complaints and no family history of breast cancer. Significant past medical history included treatment for an extramedullary retrosternal plasmacytoma 5-years prior this admission.At the time of the initial work-up for the retrosternal mass, immunoelectrophoresis showed no evidence for hyperproteinemia or paraproteinemia. Whole body bone scan was negative and a bone marrow biopsy revealed less than 5% of plasma cells. Therefore, multiple myeloma was excluded by nuclear medicine, laboratory and histology studies. The patient underwent radiation therapy (40 Gy with fraction size of 200 cGy delivered over 4 weeks) followed by chemotherapy with cyclophosphamide, cisplatin and prednisolone. The patient was followed by laboratory tests, chest roentgenography, and computed tomography annually. A bone scintigraphy was carried out after 2 years and showed no uptake patient was thereafter lost to follow-up.Five years after initial diagnosis of extramedullary plasmacytoma the patient presented with bilateral breast masses. Physical examination revealed a 3.5 cm × 2.5 cm, mass in the upper inner quadrant of the right breast and a similar 5.0 cm × 4.5 cm mass in the lower inner quadrant of the left breast. No asymmetry, skin dimpling or signs of inflammation were present. There was no axillary or supraclavicular lymphadenopathy.Mammography confirmed a well-defined 3.2 cm oval-shaped mass in the upper inner quadrant of the right breast, and a lobulated 5.5 cm density in lower inner quadrant of the left breast without any tissue distortion, inflammation and fibrotic reaction.Figure  There we99 bone scan and skull and pelvic X-rays) did not show any pathological changes. There was no evidence of anemia, hypercalcemia or renal insufficiency. However, the patient refused a second bone marrow biopsy.Excisional biopsy of the masses revealed a 5.0 (left) and 3.0 (right) well-defined, capsulated gritty mass surrounded by normal breast tissue. There was no extension from the capsulated masses to pectoral muscles or chest wall. Histopathological examination showed high-grade tumors composed of immature and mature plasma cells. Mitosis, necrosis, nuclear pleomorphism and binucleated and multinucleated plasma cells were seen. Figure  AdditionImmunohistochemical studies were performed on the paraffin embedded tissues to determine if the infiltrate had monoclonal character. The tumor cells were diffusely and strongly positive for lambda chains but negative for kappa chains. Figure The tumor cells were weakly positive for monoclonal mouse anti human placental V538C, and plasma cell markers (CD138). Nuclear prognostic marker (Ki67) showed 50% to 80% nuclear expression indicative of high proliferative activity and suggesting a plasmacytic tumor with anaplastic components Figure . Other iA retrospective microscopic review of the mediastinal mass showed similar morphology to the breast tumor. Hence, the histological diagnosis of recurrent plasmacytoma was made.The patient was treated with oral Melfalan and Prednisone. The patient has been disease free for twenty months after treatment and has showed no evidence of recurrence in the mediastinum, breast or any other region.Primary soft tissue extramedullary plasmacytoma (SEP) is uncommon and is defined as a malignant tumor of plasma cells arising in the soft tissue in the absence of bone involvement. It can occur in any organ as a solitary form of plasma cell neoplasm . AlthougWhen plasmacytoma originates from soft tissues, like the case presented here, the disease is usually associated with a relatively mild clinical behavior and long survival, suggesting that it is a truly different disease entity compared to other plasma cell tumors .et al (1999) reported that solitary extramedullary (soft tissue) plasmacytomas (SEP) are less common than solitary bone plasmocytoma (SBP), and have a better prognosis as the majority can be cured by local radiotherapy [Dimopoulos otherapy .et al (1999) reported local recurrence rates of less than 5% after radiotherapy [et al (1990) noted that the risk of distant relapse is more than 30%, which is significantly less than that seen with SBP [Liebross otherapy . Mayr etwith SBP . Progreswith SBP .Involvement of the breast with SEP is uncommon and may occur either as a solitary primary tumor or as evidence of disseminated multiple myeloma . Our patOur patient did not have any prior breast aspiration cytology. There are many tumors, which may present with plasmacytoid appearance on aspiration cytology. Tumors such as small ductal carcinoma and lobular carcinoma of breast, metastatic carcinoid, metastatic melanoma and some lymphomas may represent with uncohesive group of cells with eccentric nuclei resembling plasma cells. Hence, a plasmacytoma (with anaplastic plasma cells) may be readily mistaken for carcinoma (or other undifferentiated neoplasm) not only clinically, but also on cytological examination. This would justify excision biopsy and the use of an extended immunohistochemical panel to include such markers as cytokeratin and S-100 in the assessments. To help the cytopathologist avoid misinterpretation, clinical history and presentation are extremely helpful. Most of the errors in histopathology and cytopathology diagnosis occur when pathologist is not aware of medical history of the patient and unusual clinical presentation.This case emphasizes the importance of distinguishing a plasmacytoma of the breast from primary mammary carcinomas and other benign lesions to avoid unnecessary surgery and provide the appropriate treatment and adjuvant therapy.AK carried out excision biopsies and drafted the manuscript.MJZ did the histopathological examination and contributed to the pathological content of the manuscript.SKR is the pathologist who confirmed the diagnosis and prepared the immunohistochemical stains and illustrations. He also contributed to pathological content of the manuscriptMN followed-up the patient and contributed to the manuscript preparationAll authors read and approved the final manuscript.


Quantitative proteomics is an emerging field that encompasses multiplexed measurement of many known proteins in groups of experimental samples in order to identify differences between groups. Antibody arrays are a novel technology that is increasingly being used for quantitative proteomics studies due to highly multiplexed content, scalability, matrix flexibility and economy of sample consumption. Key applications of antibody arrays in quantitative proteomics studies are identification of novel diagnostic assays, biomarker discovery in trials of new drugs, and validation of qualitative proteomics discoveries. These applications require performance benchmarking, standardization and specification.Six dual-antibody, sandwich immunoassay arrays that measure 170 serum or plasma proteins were developed and experimental procedures refined in more than thirty quantitative proteomics studies. This report provides detailed information and specification for manufacture, qualification, assay automation, performance, assay validation and data processing for antibody arrays in large scale quantitative proteomics studies.The present report describes development of first generation standards for antibody arrays in quantitative proteomics. Specifically, it describes the requirements of a comprehensive validation program to identify and minimize antibody cross reaction under highly multiplexed conditions; provides the rationale for the application of standardized statistical approaches to manage the data output of highly replicated assays; defines design requirements for controls to normalize sample replicate measurements; emphasizes the importance of stringent quality control testing of reagents and antibody microarrays; recommends the use of real-time monitors to evaluate sensitivity, dynamic range and platform precision; and presents survey procedures to reveal the significance of biomarker findings. Traditional immunoassay platforms have very limited multiplexing capability and high sample volume requirement. The development and application of high throughput, multiplex immunoassays that measure hundreds of known proteins in complex biological matrices, is becoming a significant tool for quantitative proteomics studies, diagnostic discovery and biomarker-assisted drug development [reviewed in -4]. Two Unique, general considerations in assembling multiplexed immunoassays include: Requirements for elimination of assay cross-reactivity; configuration of multi-analyte sensitivities; achievement of dynamic ranges appropriate for biological relevance when performed in diverse matrices and biological states; and optimization of reagent manufacturing and chip production to achieve acceptable reproducibility. In contrast to traditional monoplex enzyme-linked immunoassays, generally agreed specifications and standards for antibody microarrays have not yet been formulated. A number of recent articles have started to examine certain of these issues ,6,7.Microarray immunoassays performed on planar glass slides and employing signal enhancement with rolling circle amplification (RCA), have been developed by several groups and have demonstrated usefulness in measurements of temporal and dose-dependent changes in a variety of immunological model systems and human diseases ,2,8-16; -16; 8-16I. Analytes in an applied sample bind to capture antibodies immobilized on a silanized glass surface.II. Applied secondary biotinylated detector antibodies bind to captured analytes, creating a highly specific immune complex.III. Biotinylated detector antibodies bound to the immune complex are detected with a universal anti-biotin antibody. The latter is conjugated to primer oligonucleotides that are pre-annealed to a complementary circular oligonucleotide.IV. DNA polymerase extends the 3' ends of primers around the circles, resulting in long, single stranded RCA products that remain attached to the complex.The RCA product, composed of tandem DNA repeats complementary to the circle sequence, is detected by hybridization with cyanine 5 (Cy5)-labeled complementary oligonucleotides.The present report describes initial development of standardized operating procedures, quality controls and standards for microarray immunoassays performed on planar glass slides using signal enhancement with RCA. These metrics have been tested for use in generation of data with adequate sensitivity, reproducibility and assay performance for biomarker discovery -14,16, P, P16, PaTo demonstrate the feasibility of using a multiplex immunoassay system to measure protein levels in complex biological matrices, the performance of dual-antibody, sandwich immunoassay arrays performed on planar glass slides with RCA signal enhancement was evaluated for specificity, sensitivity, reproducibility and accuracy using standardized titrations, spiked biological matrices and clinical samples. Array performance was evaluated based on ability to: measure analytes across a broad dynamic range at sufficiently low coefficients of variation (CVs); detect proteins at levels requisite to capture biologically relevant expression differences; confirm reliability of methods to normalize data to minimize platform imprecision and demonstrate the utility of generating standard curves to convert analyte MFI (mean fluorescence intensity) data into mass unit information.An advantage of arrays is the ability to measure each analyte multiple times, enhancing precision. Capture antibody spots were printed in quadruplicate on planar glass slides providing redundancy of individual analyte measurements. Data redaction was applied to raw immunoassay data to improve data quality by eliminating outlier data points. Outliers were identified by employing two subsequent statistical approaches in a step-wise manner.First, the Bland-Altman plot was used. Bland-Altman plots are often used in DNA microarray analysis to identify differences and/or replicate outliers. This involves plotting the difference between the logarithm of intensities of two replicates (M) versus the average of logarithm of intensities (A) for each analyte within an individual array . Thus, there will be 6 MvA plots for each data set to reflect the 170 analytes positioned across 6 arrays. Each MvA plot will contain 3*Ns*Na points, where 3 reflects the number of possible unique pair wise combinations of the three replicates, Ns represents the number of samples and Na defines the number of analytes measured on a given array. An example of an MvA plot produced in a project comprising 150 clinical serum samples for Array 4 with 37 analytes is shown in Figure 2) is examined for each plot. Each plot contains Na data points, where Na reflects the number of analytes. Plots with R2 values <0.95 are examined to identify the cause of the poor correlation. We have identified two major sources of poor correlation: incorrect positioning of the capture grid during image quantitation and general aberrations in image spot quality. Assigning the specific source of low correlation is accomplished by tracing back to the image data. In the case of grid misplacement, suspect data images are re-quantified. Poor correlations due to aberrant spot morphology/intensity are manually examined and removed from data set. If the R2 value does not improve as a result of outlier removal, the replicate is redacted from the data set. The sample is considered passed if there are two replicates with R2 >= 0.95. The pass rate is defined as the number of passed samples divided by the total number of samples. A run of an array is considered to be passed if 85% of the samples have two or more passed replicates.The second step of data reduction involves a linear correlation analysis. Pair-wise correlation analysis is done between all replicates of individual sample. Figure 2 values < 0.95. This process reduces throughput of data redaction, particularly on large data sets. Table In our experience, applying the MvA statistical approach first, followed by the linear correlation analysis is an efficient process to identify outliers without compromising data throughput. Since, MvA plots can be generated quickly, it allows for relatively fast redaction of significant outliers using an objective semi-automated approach. In contrast, the sample correlation analysis is considerably more labor intensive and currently requires manual investigation of each scatter plot with RIn general, for data sets with more than 40 samples, outlier removal only demonstrated small improvements in reducing average CVs across all samples. The most significant impact of outlier removal is on improving reproducibility across the three replicates of the individual samples. In our experience, outlier removal has been shown to reduce individual sample replicate CVs by 2–3 fold. This effect is directly related to improving sample correlation pass rates by by 10–20%.Many systematic factors can modify spot intensity during the process of measurement. Normalization is the process of reducing the effects of systematic variation on spot intensity. Normalization in DNA microarrays typically involves adjusting distributional summaries of data (mean, median) from each chip to common reference values. For example, one assumption could be that the average signal from each protein chip should be the same, as with DNA microarrays and the difference between replicate values is due to systematic variability in the measurement process. Unfortunately, the nature of protein antibody microarrays, configured with a multiplex of individual capture and detector antibodies, is more specialized and differentiated than that of a DNA microarray. Use of a single reference factor derived from a global value is not sufficiently refined to take into account the difference in platform configuration. In the current report, the organization of protein microarrays allows the measurement of up to 16 samples per slide (chip). This is very different from DNA microarrays where one chip represents the total collection of measured values for an individual sample.To accommodate the differences inherent to the platform, we have applied a normalization strategy based on the three major sources of technical variability observed in our system. The first type of variability relates to spot-to-spot differences observed between quadruplicate spots of the individual analytes printed within a sample well. The second level of variability can be described as the difference in measurements between wells within the same slide. The third element of variability represents the variability observed between sample wells compared across different slides. We found that slide-to-slide variability is the largest source of variation accounting for more than 70% of the total measurement imprecision (data not shown). Thus the goal of normalization is to reduce the imprecision of slide-to-slide measurement error since this represents the major source of platform variability.Normalization is performed using a system of standard controls to reduce the effect of slide-to-slide variability. A series of four standard control samples  are run in 4 wells of each slide. Each control sample represents a cocktail of the full repertoire of analytes for the given array tittered at 4 specific concentrations. The standards have been optimized at concentrations (12 pg/ml, 111 pg/ml, 333 pg/ml and 1000 pg/ml) to capture measurements across the linear range of detection for each analyte. The global average of total analyte signal for the four prepared controls is calculated across all slides run in a batch. An adjustment factor is created for each slide that reflects the difference between global intensity average for all slides and the individual intensity average based on the controls from the individual slide. The averaged pixel intensity of each spot on the slide is scaled by the adjustment factor.As an example, the average value of the adjustment factor was evaluated across a batch of 33 slides and found to have a value of 1.33+/- 0.47. The primary benefit of normalization was in reducing the replicate sample CVs. Figure A 15-point series of standardized titrations containing recombinant proteins diluted in buffer were used to evaluate platform precision. This assessment was used in the quality control of each slide lot prior to release, as well as within each client project to verify run-time analyte performance. Six replicates for each point were run in the quality control testing of each slide lot and six replicates of each point were run within each client study to generate standard curves. CVs were evaluated for each concentration of analyte across six slides. Average CVs were calculated for each analyte. Statistical summaries of CV distribution across all array 2 analytes using the standardized 15-point standard titration series are shown in Table A variance decomposition analysis was performed to reveal the extent to which platform error influenced the ability to identify biomarkers. The variance component assigned to platform error was typically found to be an order of magnitude lower than the average inter-individual variation. Figure The left panel of Figure A performance assessment of individual analytes was conducted to determine the utility of each analyte across multiple projects covering diverse disease areas. Each analyte was evaluated according to the percentage of clinical samples that fell within (W), below (B) or above (A) the linear range of detection. Tables ,7,8,9,10The development of an antibody array featuring 25–40 novel immunoassays requires extensive validation related to the comprehensive assessment of antibody cross reactivity, definition of analyte minimal detection limits (MDL) and establishing robust assay performance. Each antibody array must be validated for use with several matrices, since the latter may have different ambient analyte levels  or cross-reactivity profiles.Analyte sensitivity was assessed to identify analytes lacking adequate performance for retention on an array. Additional experiments were performed to determine the endogenous levels of each analyte. For analytes without previously reported biological values, the "0 × n" assays indicated the approximate ambient analyte level. Testing across multiple biological matrices was required, since different matrices affected the detection of analyte specific signals. The "0 × n" experiments also revealed the level of non-specific background which was influenced by the total concentration of antibody load in the detector mix. In our experience, certain plasma matrices were also more likely to generate high background when compared to matched serum samples. The impact of high generalized background is a reduced sample pass rate. When background was observed, the total detector antibody concentration could often be reduced to minimize background noise. Ultimately, a balance between reduction in background and enhancement of sensitivity was required to achieve maximal analyte performance in a mutiplex configuration.The results of the 1 × (n-1) assays identified analytes that demonstrated cross-reaction between the captured analyte and the complex detector mix prepared without the cognate detector antibody. Binding between the spiked analyte and the cognate capture that generated signal, indicated a cross-reaction to one or more non-cognate detector antibodies contained within the complex mix. In cases where non-cognate detector signal was observed, an additional series of experiments were run with the corresponding analyte tested against each of the individual detectors to identify the cross-reacting detector antibody. Since cross reaction is an additive process, the outcome of the cross reaction assessment allowed for adjustments to be made to achieve a balance between maximizing content with multiplexed array specificity. The 0 × (n-1) assays were run to provide a baseline of MFI values to compare to the results obtained in the 1 × (n-1). In addition, the 0 × (n-1) experiments also served to screen the various biological matrices for cross-reactivity with endogenous proteins.2 values obtained between the two conditions provided a measurement of the accuracy of the multiplexed system.Serum MDLs were typically found to be higher than buffer MDLs due to the presence of endogenous analyte, potential analyte-binding proteins present in the biological matrix and other possible matrix-related interferences. The assay conditions used to stress test the system under conditions of high analyte load were designed to identify cross-reaction thresholds for each of the individual analytes. MFI cut off values were used to identify significant increases in non-cognate signal that warranted removal of a feature from the array. The results provide a certain utility in predicting array performance under conditions where sample analyte concentrations exceed reported biological levels. Examples might include patient samples tested under diseased states, elevated analytes produced in stimulated cell culture supernatants or in samples exhibiting a strong drug response. The final validation involved measuring the accuracy of the multiplex assay when challenged with a high concentration of analyte. Figure Thirty years of widespread use of conventional, monoplex immunoassays has established firm benchmarks for performance in protein measurement. In the present paper, we have examined several, unique but general considerations in assembling multiplexed immunoassays with performance similar to conventional monoplex immunoassays. These include development of a comprehensive validation program to identify and minimize antibody cross reaction under highly multiplexed conditions; application of standardized statistical approaches for data handling for highly replicated assays; inclusion of standardized samples in each run to normalize sample replicate measurements; quality control of reagents and antibody microarrays; implementation of real-time monitors to evaluate sensitivity, dynamic range and platform precision; and initial procedures for identification of specific, significant immunoassay results in biomarker discovery projects involving clinical samples. Each of these will be discussed briefly.An array validation program represents the foundation of tests required to establish robust assay performance in a multiplexed environment. The most significant component in array validation is the comprehensive evaluation of cross reactivity. The vast majority of the ~5000 commonly available antibody pairs available today have not previously been evaluated for cross reactivity in a multiplexed environment. Therefore, the recommended program should include procedures that identify analytes demonstrating cross reactivity with immobilized capture antibodies as well as cross reaction that might manifest between the secondary detector antibody with a non-cognate analyte or non-specific binding to an immobilized capture agent.The performance of analytes in a multiplexed configuration should be benchmarked against the baseline, monoplex performance. This multiplexed immunoassay comparison with baseline performance, together with minimal standards for multiplexed cross-reactivity, permits determination of the practical, optimal number of array elements that can be successfully combined. In our experience, using dual-antibody, sandwich immunoassays, planar glass slides and RCA signal amplification, protein micorarrays can generally accommodate multiplexing of 25–35 analytes without an appreciable drop in individual analyte sensitivity or performance. Specifically, we have described development of six different dual-antibody sandwich immunoassay arrays, each containing 25–37 sandwich immunoassays. Since cross reactivity is an additive process, the ultimate goal is to achieve a balance between maximal multiplexing and monoplex-like performance. With exhaustive selection for antibodies without cross-reactivity in multiplexed format, it is possible to multiplex 50 sandwich immunoassays. However, this exercise is very expensive. In our experience, suspension arrays, alternative microarray surface substrates and attachment chemistries do not offer significant advantages in multiplexing while maintaining performance. We have not evaluated the impact of novel, affinity ligands on multiplexing.Additional array validation for cross-reactivity should include "stress-testing" under high analyte load to reflect conditions where analytes may be significantly over-expressed. In our experience, levels of induction of proteins in common biological matrices can be very large following drug administration or in disease states, and may induce cross-reactivity that is not observed in testing within normal biological analyte levels.Finally, array validation should be performed across all common sample matrices to examine effects on assay performance associated with endogenous analyte, matrix specific analyte binding proteins or other matrix-specific inhibitors. Absence of cross-reactivity for an immunoassay in one matrix does not always imply absence of cross-reactivity in others. The matrices for which the antibody microarrays described herein have been validated include isotonic buffers, serum, citrate plasma, heparin plasma, EDTA plasma, cell culture supernatants, amniotic fluid, sputum, and exhaled breath condensates. Several of the arrays have also been validated for use with ex vivo treated whole blood. EDTA plasma and ex vivo treated whole blood had higher levels of background signal and lower sample pass rates than other matrices.2> 0.95 range were eliminated. In order for data from sample replicates to pass and be admitted into the final data set, the overall sample replicate-to-replicate correlation for the 25–37 analytes of the array was required to have an R2> 0.95. Experience in multiplexed immunoassay measurements in samples across more than 30 research projects indicated the R2 value >0.95 to be routinely achievable and associated with high quality replicate data. In each project, the data lost through these two sequential redaction procedures was typically less than 5% of the total original data. An additional quality metric to assess the overall run performance was that at least two of the three replicates must have passed for 85% of the total samples. Runs falling short of this metric were failed and subject to repeat. The typical run fail rate was less than 3%.A significant advantage of array-based immunoassays is the ability to measure each analyte in a sample many times. Removal of outlier replicates is obligatory for microarray assays due to signal-related and morphology-based artefacts typically associated with dispersing small volumes of material on a solid substrate in a microarray format. Application of standardized statistical approaches for data redaction is superior to manual inspection and removal of outliers since operator-dependent subjectivity is minimized and throughput is greatly increased. The data redaction procedures described herein employed two, separate steps: Bland-Altman plots and linear correlation analysis. Bland-Altman plots were employed first and identified 99% confidence intervals for all collected data points. This enabled rapid identification and elimination of the outlying 1% of the data with minimal human intervention. This was determined to be an objective, reproducible redaction procedure that greatly reduced time and effort associated with the subsequent, second data redaction step of linear correlation analysis. Linear correlation analysis required performance of 3 replicate assays on each sample, and manual inspection of the series of 3 scatter plots generated from pair-wise correlations of these 3 sample replicates. Individual replicate points for each specific analyte that fell outside the RWithin-run controls were employed to account for the effects of systematic variation in replicate measurements. Variation was identified at three levels based on the unique configuration of the 16 sample well microarray chip. The lowest level of variability was observed between the quadruplicate spots of an individual analyte measured within a single sample well. The next level of variation was described as the difference between replicate analyte values measured in different wells located within the same slide. The highest level of variation was associated with measurements taken from a single sample applied to multiple wells positioned across different slides within a run. Since slide-to-slide variation demonstrated the highest system variation, a series of four controls were designed to minimize the impact on sample replicate measurements. The four controls contained all analytes for that array at four concentrations spread across the dynamic range. The four controls were run on every slide within a project and used to generate a global average of total analyte signal. Based on the global average, each individual slide was assigned an adjustment factor to compensate for the slide specific intensity bias. The analyte signal from each individual slide could then be scaled by the adjustment factor to normalize the intensity values between the sample replicates positioned across different slides. In addition, it is possible to use a blocking experimental design, intentionally positioning sample replicates across different slides and different slide locations to eliminate the potential for a slide-specific or location-specific intensity bias. An example of the latter might have been the well at the corner of a slide. Replicate measurements in conjunction with a mechanism to normalize systemic variation results in the production of high quality data required for maximal sensitivity in the identification of significant differences between samples in multiplexed immunoassays. An additional benefit of inclusion of standardized controls run across all slides of every project is the ability to standardize data, for example in mass units, and enable data comparisons between runs, between days and between projects. Such comparisons are necessary when projects constitute large numbers of samples or when it is desired to create a relational database of assay results. Our platform described herein, for example, can perform triplicate measurements on up to 200 samples in a single run.Quality control of approximately 1200 individual reagents is necessary in order to provide consistent performance of 170 immunoassays on the array platform described herein. These reagents, unfortunately, have widely different shelf life and storage conditions. Stringent quality control procedures specifying performance metrics associated with these reagents were required to achieve reproducible array performance across hundreds of slide lots and reagent sets. Each new lot of a given component was benchmarked to an earlier lot to verify performance. Analyte intensity, dose-response curve, LLD/ULD absolute values, dynamic range and background signal were evaluated in fuctional tests performed on all assay components. Historical performance was monitored by comparing running averages obtained from earlier lots to prevent performance change over time. These procedures were made practical by assembling cocktails of reagents for each step in an assay, dispensing these in single-use aliquots, establishing optimal storage conditions and shelf life, and performing regular  quality checks on aliquots. Implementation of such procedures required use of a laboratory information management system.The utility of integrating real-time platform performance monitors cannot be understated. Given the complex nature and potential instability of biological reagents associated with a multiplex antibody array, it is critical have a program in place to evaluate performance beyond the quality control release. Real time monitors measure performance of controls under conditions identical to the test samples and reflect a second level verification of assay performance. Our test system employed a series of monitors to capture precision metrics that would create a flag to review the data if the specifications were not met. The requirements included mean coefficients of variation of assay values for controls be less than 15% and for sample replicates be less than 25% for project samples run within a batch. Failure to achieve these metrics indicated a problem related to the performance of the manufactured slides and/or reagents or a technical failure associated with sample handling or assay execution. 15-point standardized titrations were also performed on 6 slides in every run in order to captured detail related to analyte dynamic range, LLQ/ULQ values, dose response behaviour, and background signal that provided a comprehensive assessment of real time platform performance. The detail of the performance assessment was included in final reports for each project to verify data quality and generate confidence in the data generated from a highly complex assay.Evaluating data generated from multiplexed immunoassays for utility in systematic identification of significant differences between samples, or "biomarker discovery", is an important step in understanding the true platform performance. One of the procedures that revealed the sensitivity of the platform for biomarker discovery was variance decomposition analysis for each project. Variance decomposition analysis examines the magnitude of individual components of platform variation and how they compare to analyte variation between samples or individuals. In our experience the platform error of the system described herein was generally an order of magnitude lower than the heterogeneity observed between samples or individuals of the same test group. The utility of this test is in revealing the extent to which platform error impacts the ability to discover moderate expression level differences between samples that are reflective of biological change. Platforms with lower precision will have less sensitivity for detection of relevant differences between samples and will discovery only a subset of the markers that would have been identified with a more precise system.Finally, a global performance assessment should be performed across multiple projects covering diverse disease areas to gain a solid understanding of the platform utility. An evaluation of this type can be used to identify assays that will not identify differences in expression between samples because they are not sufficiently sensitive, unable to generate sufficient dynamic range given the window of expression, or reveal high endogenous abundance producing assay saturation artefacts. In addition, specific assays that have appropriate sensitivity and dynamic range may be constitutively expressed and therefore poor biomarker candidate analytes for certain disease or treatment effect studies. This analysis may be used to direct efforts to continue to optimize the survey platform in order to generate the highest value in identifying biomarkers using a quantitative proteomic approach.Protein microarrays offer the ability to simultaneously survey multiple protein markers in an effort to develop expression profile changes across multiple protein analytes for potential use in diagnosis, prognosis, and measurement of therapeutic efficacy. The current report details certain minimal standards, use of which was found to be necessary to generate the requisite specificity, sensitivity and reproducibility to discover biomarkers. Results revealed that a multiplex system could be operated with high analyte specificity, adequate detection sensitivity and sufficiently broad dynamic range to capture expression differences across diverse disease and therapeutic areas.Raw soda-lime glass slides (1" × 3") prepared with a Teflon mask configured to provide 16 individual sample wells and an etched barcode for traceability were subjected to visual inspection to identify imperfections that might translate into printing and/or scanning artifacts. Slides with scratches, surface contamination or defects in the applied Teflon mask were identified through a visual examination using a long wavelength inspection lamp equipped with a 532 nm filter. The inspection also failed slides that did not meet stringent dimensional specifications, required for downstream printing and automated assay conditions.Slides passing the visual inspection were silanized with 3-cyanopropyltriethoxysilane according to procedures previously described . MeasureCapture antibodies prepared as previously described  were priEach printed array contained 256 spots representing 64 individual elements printed in quadruplicate. Each array contained 25–40 capture antibodies spread across production chips 1–6, generating a panel of 170 survey analytes. The balance of the elements was reserved for internal assay controls. Each printed array contained multiple copies of an element called BLANK, containing the components used in capture antibody preparation. Blanks were used to survey non-specific sample background within each well. Other printed controls included a series of biotinylated mouse IgG calibration standards to monitor RCA signal amplification and a third control that acted as a monitor for spot contamination resulting from carry-over between sequentially printed features.Preparations of standardized multiplex analyte titration series were manufactured using recombinant analytes diluted in buffer that covered the range from 12 pg/mL up to 81 ng/mL at 14 discrete points along with two zero analyte buffer blanks. These titration points were distributed among the sixteen available wells on a slide . Manual immersion washes were substituted with pipette delivered solutions finely tuned to control pipette tip aspiration and delivery position above printed slide wells and to carefully control liquid application and aspiration speeds to minimize disruption to the assembled immunosandwich complex. Incubation times were increased from 30 to 45 minutes for two of the assay steps  and the number and volume of washes between steps increased from 2 to 4–5 and from 20 uL to 30 uL respectively. A Tecan LS200 unit was used to scan the slides. Microarray images were quantified using image capture software (ImageGrabber) developed in-house.Frozen serum samples from over 800 clinical patients were thawed, centrifuged to remove particulate matter and mixed with 0.25 mg/ml Heteroblock (Omega), 0.25 mg/ml IIR (Bioreclamation) and 0.1% Tween-20 prior to the assay. Twenty microliters of serum was applied to each well.2(Rep1/Rep2) versus the average of the log intensities (A=log2((Rep1*Rep2))/2) for each of the replicates across all analytes. Patterns were visualized using fitted curves from robust local regression with applied visual cues to identify a 99% confidence interval. All outliers in the MvA plot outside of the interval  were automatically removed from analysis. The MvA scatter plots also allowed the user to highlight subsets of points on the plot and investigate patterns of intensity differences observed between replicate values. In cases where redaction of an entire replicate  was too stringent, individual spots could be removed using an in-house developed software tool (Terminator) to visually inspect aberrant data points. Data redaction using this method was performed on a limited basis to remove individual spot outliers with poor circularity, non-uniform pixel intensity or missing spots.Data points producing outlier events as a result of missing spots, spots with poor morphology, or printed features demonstrating high pixel outliers were removed using a combination of automated and manual methods. MvA plots, were generated by plotting the difference of the log intensities (M=log2) value cutoff. An ideal microarray, when compared to its identical replicate, would have a R2 value of 1. Any comparison producing values lower than the cutoff would result in at least one failed replicate. Individual sample correlations were generated by plotting analyte MFI values  from each replicate against the other replicates individually covering all combinations of replicates over the 25–37 analytes within the array. The R2 values obtained for the three plots were manually reviewed to identify failed sample replicates. Only sample replicates with R2 values >0.95 for replicates run within a day or R2 values >0.90 for replicates run across multiple days passed the correlation QC. A summary of the overall sample replicate pass rate monitored the number of failed replicates observed across each of the individual arrays. Project performance specifications required that >85% of all study samples had at least 2 reported replicates.As a quantitative QC measure, data review included a sample replicate correlation assessment with a predefined correlation coefficient  scale to generate within-slide titration curves. Linear regression coefficients (slope and intercept) were calculated between individual titration curves from each slide to generate an "average" titration curve. Calculated slope and intercept were used to transform averaged analyte values for each sample well. Data normalization was performed on the data set after outlier removal.A standardized precision assessment was performed on each run to monitor assay performance with respect to; within well variation (based on mean coefficient of variation (CV) observed between quadruplicate printed spots for all features across all sample wells of a project) and between-slide variation . The mean and median CVs with standard deviations were also metrics included in the precision assessment. The precision assessment was performed as a quality control using the 15-point titration calibrators to qualify new slide lots and generate quality metrics for each client project.Mean fluorescent intensity (MFI) values, on a logarithmic scale, from the 3 replicate measurements of the 15 point standard titration series were used to generate precision profiles to define the upper and lower limit of quantitation (ULQ, LLQ) within a predefined concentration CV . To do tThe VARCOMP procedure of SAS (SAS Institute), was used to obtain estimates of the variance components in a mixed model. The fixed effect variable represents variance observed in different groups in the study, for example groups of healthy versus diseased individuals. Random effects were represented by unique sample identifiers nested within levels of a fixed variable. This component of variance represented within-group differences associated with patient-to-patient variability or disease heterogeneity. The residual variance represented the platform error.Assay sensitivity was determined in two series of experiments. Initial testing to identify analyte cross-reactivity was performed in a configuration where all printed capture antibodies are surveyed in a "1 × n" format, representing a single recombinant analyte tested against all (n) detectors across multiple matrices (serum, heparin plasma, citrate plasma, EDTA plasma and buffer). Capture antibodies that revealed binding to non-cognate antigens were removed or replaced with suitable alternatives. Analytes that demonstrated low signal across all matrices were removed. If signals were low in buffer, a comparison was made with signals obtained in serum or plasma to determine if the endogenous analyte level was detectable and determine if depressed signals were due to analyte instability in a non-biological matrix. Assessment of analyte endogenous level was performed using a "0 × n" format where unadulterated serum and plasma (heparin, citrate, EDTA) are assayed with the full complement of detector antibodies for a given array.Two conditions were examined to study potential cross-reactivity between the complex detector antibody mixture and the immobilized capture analyte. The first condition included a 1 × (n-1) format in which 1 analyte was tested in the presence of all detectors minus the detector antibody specific to the added analyte (n-1). In the case of an array containing 40 printed features, 40 unique detector antibody cocktails are prepared containing 39 of the detector antibodies found in the complex mix, with each mix containing all but one of the 40 corresponding detectors. The 40 individual reaction mixes are added to specific arrays after the arrays were incubated with the antigen corresponding to the missing detector. The second condition represented the 0 × (n-1) format where no analyte was added in the presence of all detectors minus the detector specific to the analyte under examination. In each case the analytes were spiked in buffer, serum, and plasma (heparin, citrate, EDTA) at a fixed analyte concentration of 50 ng/ml.Single analyte titrations were prepared in buffer, serum and plasma (heparin, citrate, EDTA) to assign a minimum detection limit (MDL) for each analyte based on a 95% confidence interval above background. The format of the experiments included an n × n design, where all analytes were run in the presence of all detectors. Then, using a 1 × n format, where only one antigen was added to an assay containing all detectors (n), each analyte was tested at 0X, 10X, 50X, and 100X MDL across the same test matrices to identify non-cognate cross-reaction under high analyte load. Additional antigen titration experiments were run to compare the performance achieved in the presence of a single antigen (1 × n) to one in which all analytes were present (n × n).MFI: Mean Fluorescence Intensity.RCA: Rolling Circle Amplification.CV: Coefficient of Variation2: correlation coefficientRLLQ: lower limit of quantitationULQ: upper limit of quantitationMDL: minimal detection limitsSD: standard deviationL.T. Perlee, J. Christiansen, B. Grimwade, S. Lejnine, V. Tchernev and M. Sorette were employees of Molecular Staging, Inc. and D.D. Patel and S.F. Kingsmore have received consulting fees.RD oversaw the manufacturing of reagents, JC established standardized quality control testing procedures, MS implemented assay automation and oversaw all clinical testing. BG was responsible for data curation, SL performed statistical analysis. MM and WS contributed to array develoment. SFK, VTT and DDP were involved in study design, LTP in project execution and LTP, SL, JC and SFK in manuscript preparation.


Antimicrobial resistance is particularly harmful to infectious disease management in low-income countries since expensive second-line drugs are not readily available. The objective of this study was to implement and evaluate a computerized system for surveillance of antimicrobial resistance at a tertiary hospital in Tanzania.A computerized surveillance system for antimicrobial susceptibility (WHONET) was implemented at the national referral hospital in Tanzania in 1998. The antimicrobial susceptibilities of all clinical bacterial isolates received during an 18 months' period were recorded and analyzed.The surveillance system was successfully implemented at the hospital. This activity increased the focus on antimicrobial resistance issues and on laboratory quality assurance issues. The study identified specific nosocomial problems in the hospital and led to the initiation of other prospective studies on prevalence and antimicrobial susceptibility of bacterial infections. Furthermore, the study provided useful data on antimicrobial patterns in bacterial isolates from the hospital. Gram-negative bacteria displayed high rates of resistance to common inexpensive antibiotics such as ampicillin, tetracycline and trimethoprim-sulfamethoxazole, leaving fluoroquinolones as the only reliable oral drugs against common Gram-negative bacilli. Gentamicin and third generation cephalosporins remain useful for parenteral therapy.The surveillance system is a low-cost tool to generate valuable information on antimicrobial resistance, which can be used to prepare locally applicable recommendations on antimicrobial use. The system pinpoints relevant nosocomial problems and can be used to efficiently plan further research. The surveillance system also functions as a quality assurance tool, bringing attention to methodological issues in identification and susceptibility testing. Exaggerated and irrational use of drugs, availability of antibiotics without prescription, the use of pharmaceuticals of doubtful quality and the HIV epidemic may all contribute to the current worldwide surge in antimicrobial drug resistance. Emerging resistance to antimicrobial drugs increases morbidity and mortality by hampering the provision of effective chemotherapy, and makes treatment more costly -3. The sIt is widely held that surveillance of antimicrobial susceptibility is fundamental to combat the emergence of resistance . SurveilThis paper describes the experience with the implementation of a computerized surveillance system for antimicrobial drug susceptibility at Tanzania's major referral hospital, and its use to analyze the susceptibility patterns of 7621 consecutively recorded clinical bacterial isolates.The study was performed at Muhimbili National Hospital (MNH), Dar es Salaam, Tanzania. With more than 1000 beds, MNH is the largest hospital in the country and serves as a national referral and university teaching hospital, as well as a primary and referral hospital for a population of approximately 3.6 million in the Dar es Salaam area. The Department of Microbiology and Immunology at MNH examines specimens from inpatients and outpatients at MNH, and from a number of nearby hospitals. Bacteriological cultures are performed on more than 23,000 specimens per year.st 1998 to December 31st 1999 were recorded and analyzed. The specimens examined included urine, pus/secretions , blood, cerebrospinal fluid, other body fluids, stools and other specimens. Mycobacteria and anaerobic bacteria were not included in the study. Apart from the WHONET software, we used Stata 8.0 for Macintosh (Stata Corporation, College Station, Texas, USA) to evaluate differences of proportions by Fisher's exact test .A free-of-charge software for the surveillance of antimicrobial resistance   was implS. aureus NCTC 6571, E. coli NCTC 10418 or Pseudomonas aeruginosa NCTC 10662. The isolates showing intermediate resistance were few and were grouped together with sensitive isolates for the purpose of data analysis. Either methicillin or oxacillin disks were used to test for methicillin-resistance in S. aureus, the results being considered equivalent and interchangeable in the data analysis. ß-Lactamase testing was not routinely performed. The susceptibility of pneumococci to penicillin was examined by the use of penicillin 2 μg disks. Commercially produced antibiotic disks, mostly obtained from Oxoid Limited, were used, however, in some instances, antibiotic disks, prepared locally were used due to financial constraints. The Department of Microbiology and Immunology participates in an external quality assessment program in bacteriology led by the World Health Organization-collaborating centre, the National Institute for Communicable Diseases (NICD), Johannesburg, South Africa. The Department of Microbiology and Immunology at our hospital receives bacterial strains from NICD, performs species identification and antimicrobial susceptibility testing, and report the results back to NICD.The specimens were cultured and the bacterial isolates identified using standard microbiological methods as described in Mackie & McCartney Practical Medical Microbiology . SusceptWe evaluated the strengths and shortcomings of the surveillance system in our setting, particularly in terms of how well it performed in its main application areas, providing locally applicable data to guide empiric therapy, monitoring antimicrobial susceptibility trends, detecting the emergence and spread of new resistance traits and as a tool for quality assurance. We also assessed the cost-implications of implementing the surveillance program in our setting. We considered direct costs, such as the purchase of equipment, and indirect costs, such as those related to the running of the laboratory, including human resources. We also comment on the benefits of the surveillance system related to both direct patient care and long-term implications of containing antimicrobial resistance.Bacillus spp. were recovered from 22.0% (n = 447) and 6.9% (n = 141) of the blood cultures, respectively. Furthermore, five Candida spp. isolates and one Cryptococcus neoformans were recovered. Among the 49 Salmonella isolates, two were identified as S. Typhi, 16 as S. Typhimurium, 16 as S. Paratyphi B and one each as S. Paratyphi C, S. Enteritidis and S. Arizonae. Twelve Salmonella isolates were not serotyped. Among the 41gonococcal isolates, 28 (68.3%) were from genital swabs. Eleven (26.8%) gonococcal isolates were obtained from the neonatal ward, out of which 4 were specified as from eye discharge.A total of 7617 bacterial isolates were registered during the study period, of which 67.4% (n = 5134) were Gram-negative and 32.6% (n = 2483) Gram-positive. Table Specimens from inpatients and outpatients contributed to 53.2% and 31.9% of the isolates, respectively. A further 6.0% were obtained from specimens from other hospitals in Dar es Salaam, while 8.8% were obtained from other or unknown locations. Among the isolates from inpatients, 36.5% were obtained from the Department of Pediatrics, 28.4% from the neonatal section and 8.1% from the other pediatric wards. The other isolates came from the Departments of Surgery (22.4%), Internal Medicine (16.6%), Obstetrics and Gynecology (9.8%), the Intensive Care Unit (4.9%) and other locations (9,8%). For 4900 isolates, the age or the estimated age group of the patient was known. Of these, 23.6% (n = 1155) were from neonates (≤ 1 month old), 6.8% (n = 335) from children aged one month to seven years, and 69.6% (n = 3410) from adults or children older than 8 years.Salmonella isolates (data not shown). The majority of Pseudomonas aeruginosa isolates was susceptibility-tested to gentamicin only, to which 4.3% (15/350) were resistant. Among the isolates of Neisseria gonorrhoeae, 70.0% were resistant to penicillin, 45.2% to tetracycline, 59.3% to trimethoprim-sulfamethoxazole, 5.9% to erythromycin and none was resistant to spectinomycin, fluoroquinolones or amoxicillin-clavulanate (data not shown).Tables E. coli from inpatients than in those from outpatients as shown in Table Klebsiella spp. from inpatients were more frequently resistant to gentamicin and trimethoprim-sulfamethoxazole than isolates from outpatients.Comparison of resistance patterns of isolates obtained from inpatients and outpatients at MNH did not show large differences. However, ampicillin resistance was more frequent in urinary isolates of Klebsiella spp. were indeed more frequently resistant to gentamicin than those from other specimen types. A significantly greater proportion of blood culture isolates of S. aureus were resistant to tetracycline than among those from other specimen types, whereas for penicillin the isolates from blood cultures were resistant in a lower proportion than the others.Comparison of resistance patterns in isolates blood cultures with those from other specimen types showed apparent great differences for some drugs, however, in most cases the number of blood culture isolates were few and did not show statistically significant differences. However, as shown in Table A great number of bacterial isolates were recorded in the system. All age groups and both inpatients and outpatients were represented in the study. More than a third of the isolates were from outpatient populations from the Dar es Salaam area, however we cannot exclude the possibility of a selection bias in favour of patients with infections caused by resistant organisms, since many patients get treatment at primary health facilities before reaching MNH. We do not know how well the rural population is represented in this material, but we assume that the outpatients in the study are mostly from the Dar es Salaam area. Ten percent of the isolates represented systemic infections, i.e. isolates from blood cultures and spinal fluid. The susceptibility test results were recorded as interpreted values (i.e. "R" (resistance), "I" (Intermediate) or "S" (susceptible)) and not as inhibition zone diameters. In this study, no molecular techniques were available for the detection of resistance genotypes and evaluation of genetic relatedness of bacterial isolates.The direct cost of implementing the surveillance system was limited to the purchase of a computer at approximately 1000 Euro. However, less expensive second-hand computers would be sufficient. The software was downloaded free of charge from the WHO website. The indirect costs of running this surveillance program are related to human sources for operating the software, including data entry and analysis, and the costs of the susceptibility testing activities. It is difficult to separate these indirect costs from the costs of running the daily laboratory activities. In our setting, a laboratory technologist from the department took on the task of operating the software in addition to her regular duties. In our experience, for a hospital of our size, it is recommendable to allocate approximately 50% of a laboratory technologist position to operating the surveillance software. In our setting, this would translate into a monthly cost of approximately 100 Euro for the department. The surveillance system is dependent on susceptibility testing of acceptable quality. The susceptibility testing incurs costs related to human resources and the purchase of laboratory reagents including antimicrobial disks and agar media. Implementing a surveillance system may increase these costs by focusing on the importance of quality reagents. However, since the susceptibility testing activities are an integral activity of the department, which would have been performed regardless of the surveillance system, we choose not to attribute their costs to the surveillance system in this context. The benefits of a surveillance system are difficult to quantify, but are of potentially great magnitude. Foremost, surveillance data may improve empiric therapy for infections and thus save lives and reduce suffering. It may reduce treatment costs by enabling the use of the least expensive effective drugs. Additionally, surveillance systems may contribute to containing or reducing antimicrobial resistance, which in the long term perspective may have great benefits in reducing morbidity and mortality, and diminish the need for expensive second-line antimicrobial agents.The strengths and weaknesses are elaborated on in the Discussion part.Experience from the World Health Organization's External quality assurance system for antimicrobial susceptibility testing has shown that disk diffusion testing is suitable for routine surveillance . HoweverE. coli, Klebsiella spp., Proteus spp. and Salmonella. Chloramphenicol may fail to cure as much as a quarter of infections caused by Salmonella and half or more of infections caused by E. coli, Klebsiella spp. and Proteus spp. Fluoroquinolones appear to be the only reliable drugs for oral treatment of infections caused by common Gram-negative bacilli, whereas gentamicin and third-generation cephalosporins remain useful for parenteral therapy.Consistent with observations from a number of other countries in the region -15 and eS. aureus, consistent with previous data from the same hospital [The study showed a very low prevalence of methicillin-resistant hospital ,18. Whilhospital . It is rhospital -21. Whilhospital ,23, the hospital  from 199Recommendations for antibiotic treatment of serious bacterial infections such as bloodstream infections and meningitis should preferably be based on knowledge of the prevalence and antimicrobial susceptibility patterns of pathogens isolated from blood and spinal fluid. While a fair number of bacterial isolates were tested in the current study, the number of blood culture isolates was limited (n = 329, excluding the CoNS isolates). As shown in Table E. coli and gentamicin and trimethoprim-sulfamethoxazole resistance in Klebsiella spp. were more frequent in urinary isolates from inpatients than from outpatients. Apart from that, there were no dramatic differences between isolates from inpatients and outpatients. The data from the study should be representative for both the hospital setting and to some degree the population in Dar es Salaam. However, the majority of the population of Tanzania lives in rural areas, where resistance patterns may be substantially different. Thus one should be cautious to extrapolate the results of the current study to be valid for populations in the countryside.It is important to specify for which population the surveillance data are valid. At our hospital, specimens from both inpatients and outpatients were examined. The hospital is to a great extent used as a primary hospital for the population in the Dar es Salaam area. However, among the cases coming to the hospital, there may be a degree of selection of patients with infections caused by resistant microbes, since many patients rely on health centers and pharmacies to cure simple ailments, and only come to the hospital when primary treatment fails. The study found that a few resistance traits, such as ampicillin resistance in E. coli has increased from zero in 1978–79 [E. coli has increased from 2% in the late seventies [Certain trends in antimicrobial susceptibility could be identified by comparison with data from other studies. While resistance to ampicillin, tetracycline and sulfonamides in Gram-negative bacteria was frequent already in the seventies ,27, it i 1978–79  and 8% ieventies  to 20% aeventies .E. coli and Klebsiella spp. were tested for susceptibility to third-generation cephalosporins and other methods for detection of ESBL (double disk synergy test, Etest, PCR) were not available.Resistance to gentamicin is common in Gram-negative bacteria with extended-spectrum beta-lactamases (ESBL), sometimes in as much as 96% of isolates . Such anP. aeruginosa the rate of gentamicin-resistance has increased, from zero in the seventies [S. aureus isolates in this study. However, the rate of tetracycline resistance (49%) was lower than reported from the same hospital in 1979 (57%) and 1982 (74%) [Vibrio cholerae, the use of the drug was subsequently greatly reduced, and this may have contributed to a concurrent decline in the rate of tetracycline-resistance in an unrelated species such as S. aureus.Also in eventies  to 4% in82 (74%) . In the 82 (74%) . Due to For meaningful comparison of data from different studies, whether from the same or different laboratories, the same method of susceptibility testing should preferably be employed. In our laboratory, the same method has been used for a number of years. The WHONET software features a number of sophisticated ways to analyze susceptibility information based on the measurements of inhibition zone diameters. Recording the diameter of the inhibition zones in disk diffusion testing is generally recommended , and mayFurthermore, variations over time in the battery of antibiotics tested makes comparison of data less useful. Laboratories in low-income countries are sometimes vulnerable to this because of unreliable supplies of antibiotic discs.S. aureus and ESBL in Gram-negative bacteria. The current surveillance indicated that methicillin-resistance is rare in S. aureus at the hospital. Ideally this should be confirmed with PCR-based methods to detect the mecA gene. Likewise, the disk diffusion testing showed the presence of resistance to ceftazidime in Gram-negative isolates, albeit at a low rate, which calls for further investigation with regard to the possible presence of ESBL. Our laboratory did not employ molecular methods for detection of resistance genes on a routine basis, but a recent study showed low prevalence of methicillin-resistant S. aureus (MRSA) [Disk diffusion testing may give indications of emerging resistance traits such as methicillin-resistance in s (MRSA) . ResistaKlebsiella spp., which may suggest possible nosocomial spread. The analysis of antibiograms did not produce convincing evidence of clonal patterns spread of bacterial isolates, possibly partly due to the variations in the battery of antibiotics tested. Molecular methods for the evaluation of the genetic relatedness of bacteria were not available in this study.The WHONET software is well suited to analyze antibiograms in order to detect suspicious nosocomial outbreaks. These functions too are dependant on the use of a consistent battery of test drugs, and also works better when results are entered as actual values for MIC or zone diameters, as opposed to the interpreted value ("S", "I" or "R"). In our hospital, comparison of resistance rates did not show dramatic variation between isolates from inpatients and outpatients. The exception was a trend for more frequent gentamicin-resistance in inpatient isolates of Gram-negative bacteria, particularly in vitro methods are followed, and only in Europe the number is at least ten [In vivo clinical assessment is of great importance in understanding bacterial drug resistance and the gold standard for evaluating resistance in malaria parasite. The multitude of methods employed for antimicrobial susceptibility testing has to some extent hampered the meaningful sharing and comparison of resistance data among countries. Recently, much work has been done in Europe to harmonize resistance surveillance efforts across country borders [In 2002 a total of 880 laboratories in 76 countries across the world used the software, including 41 laboratories in 4 African countries. The WHONET system has been implemented at MNH since 1998. Unfortunately, there is no international consensus on a recommended method for antimicrobial susceptibility testing. Worldwide at least twelve different east ten . Furthereast ten . In addi borders ,34. WhilStreptococcus pyogenes were reported as resistant to penicillin. This was subsequently double-checked, and consulting the laboratory bench-book we found that clerical errors were the explanation for this. The use of the surveillance software enabled the easy detection, investigation and correction of such errors, and consequently may contribute to increase the attention to quality issues and generally improve the performance of the lab. The current surveillance project highlighted some methodological issues, most of which were caused by budgetary limitations, such as the occasional use of locally made antibiotic disks and limitations in the identification of organisms due to lack of reagents.The implementation of the surveillance system brought focus on methodological issues, including microbial identification and susceptibility. The WHONET software has built-in functions to alert the operator if isolates with unexpected resistance patterns are entered. During the surveillance exercise in our laboratory, it was discovered that four isolates of Routine surveillance makes use of available large data sets at little additional cost and may be representative for a greater part of the population. However, often it is necessary to supplement the routine surveillance with ad hoc studies aimed at investigating particular problems. While ad hoc studies generally are more expensive to conduct, they allow for the use of more advanced and expensive laboratory methods and are better at targeting particular populations of interest. The current surveillance study identified a need for more data from bloodstream infections in order to provide reliable guidance for the treatment of serious bacterial infections. As a consequence of this, we started a study of bloodstream infections with the pediatric department at the hospital. Another laboratory-based research was started to ascertain the finding that methicillin-resistance in staphylococci is still relatively infrequent at this hospital.) in Tanzania.Resistance surveillance is a platform from which to promote focus on antimicrobial resistance issues, both within the hospital and the medical community, but also among the general population. In conjunction with the surveillance exercise, we have highlighted issues regarding antimicrobials and resistance in local newspaper letters , and theThe study suggests that laboratories, which perform susceptibility testing, can gain useful information on antimicrobial susceptibility with a minimal budget. As appropriate software can be obtained free-of-charge, the main cost of the surveillance system is associated with purchasing a computer. However, there are other, indirect costs, which may be attributed to the surveillance program depending on the situation of the laboratory, such as running costs for microbiologic procedures, including susceptibility testing. Particularly, it is important to ensure availability of antimicrobial discs of satisfactory quality. A susceptibility surveillance system also implies the need for some additional human resources for data entry and analysis. In our experience, it is recommendable to allocate approximately 50% of a laboratory technologist position to this task. While the WHONET program is excellent for entry, analysis and reporting of resistance data, the software is not intended to function as a complete patient management system for the laboratory. Data can be transferred from other databases into WHONET by the use of a complementary software called BacLink . However, in laboratories such as ours, where the management of patients' laboratory tests (i.e. receipt of specimens and laboratory forms, inscription in registers, return of test results, etcetera) is handled manually via register-books, the data must be punched into WHONET by hand. Since the WHONET database is not used directly for patient management, the surveillance activity tends to become less integrated in the clinical routine work than it should. Thus, although the program performs its task very well, in a long-term perspective, a surveillance system that is integrated with a patient management system might be more sustainable. It is difficult to quantify the potential benefits of a well-functioning surveillance system. However, we are fully convinced that the modest costs of the surveillance program are highly justified since the data generated may improve empiric therapy, help contain or prevent the further emergence of antimicrobial resistance, decrease the need for expensive second-line antimicrobial drugs and, ultimately, save lives and reduce suffering.It is imperative to preserve the effectiveness of common antibiotics by promoting rational use of antibiotics based on sound knowledge of local resistance patterns. In a hospital with bacteriology services, the implementation of a computerized surveillance system is a low-cost tool to make use of available resistance data. In our hospital, the resistance surveillance system has generated information on resistance patterns that is useful as guidance for empiric therapy of infections. It can help alert clinicians of trends of antimicrobial resistance, guide drug-policy decisions and facilitate rational use of drugs to prevent the further emergence of antimicrobial resistance. The surveillance system has also served as a quality assurance tool and led to increased focus on antimicrobial resistance and prudent use of drugs. There is need for more data from blood cultures for reliable guidance for the treatment of severe, systemic bacterial infections. For antibiotic policy recommendations to be applicable for the general population, more information is needed from outpatients and rural areas.There is limited information on antimicrobial resistance trends on the African continent. Only four African countries use the WHONET system for antimicrobial resistance surveillance, although some countries may use other similar software. Recently much work has been done to establish consensus and a more standardized approach to resistance surveillance in Europe . SusceptThe authors declare that they have no competing interests.BB was the principal investigator, participated in the planning and execution of the study, performed data entry and data analysis, and was the main responsible author. DSMM, WU, SYM and AD participated in the planning of the study and contributed to the writing process. MM contributed to designing the WHONET database, performed data entry and microbiological work, and contributed to the writing process. SH participated in the writing. NL was the project coordinator and participated in planning, data analysis and writing.The pre-publication history for this paper can be accessed here:


Birds have smaller average genome sizes than other tetrapod classes, and it has been proposed that a relatively low frequency of repeating DNA is one factor in reduction of avian genome sizes.Gallus gallus) autosomes were quantified and compared with those in human autosomes. In the chicken 10.3% of the genome was occupied by DNA repeats, in contrast to 44.9% in human. In the chicken, the percentage of a chromosome occupied by repeats was positively correlated with chromosome length, but even the largest chicken chromosomes had repeat densities much lower than those in human, indicating that avoidance of repeats in the chicken is not confined to minichromosomes. When 294 simple sequence repeat types shared between chicken and human genomes were compared, mean repeat array length and maximum repeat array length were significantly lower in the chicken than in human.DNA repeat arrays in the sequenced portion of the chicken (The fact that the chicken simple sequence repeat arrays were consistently smaller than arrays of the same type in human is evidence that the reduction in repeat array length in the chicken has involved numerous independent evolutionary events. This implies that reduction of DNA repeats in birds is the result of adaptive evolution. Reduction of DNA repeats on minichromosomes may be an adaptation to permit chiasma formation and alignment of small chromosomes. However, the fact that repeat array lengths are consistently reduced on the largest chicken chromosomes supports the hypothesis that other selective factors are at work, presumably related to the reduction of cell size and consequent advantages for the energetic demands of flight. Genomes sizes (as measured by the DNA mass per diploid nucleus) are smaller on average in birds than in other tetrapod classes, and genome sizes within the class Aves show less variation than those of other tetrapod classes ,2. It haAn alternative to the hypothesis that the reduced genome size is adaptive is the hypothesis that it resulted from an event of genomic DNA loss that was fixed in the ancestor of all birds due to genetic drift. The fixation of even a deleterious mutation is possible if the population undergoes an extreme bottleneck . Some auGallus gallus) and human (Homo sapiens) genes. They found that corresponding introns were significantly shorter in chickens, indicating that numerous independent deletions have occurred in the introns of birds. These results support the hypothesis that genome size reduction in birds is adaptive, since it is unlikely that such a large number of independent deletion events were due to chance alone. Additional evidence in support of the adaptive hypothesis is provided by the observation that a secondary increase in genome size has occurred in avian lineages which have become flightless or have reduced flying ability [In order to decide whether genome reduction in birds was adaptive or due to a random event, Hughes and Hughes  compared ability .It has been suggested that an important factor in genome size reduction in birds has been that birds have lower levels of repetitive DNA than other vertebrates . GenomesThe sequencing of a substantial portion of the chicken genome has made it possible to examine quantitatively the distribution of repeating sequences on different chromosomes in the genome. Here we compare the distribution of repeats on 28 sequenced autosomes of chicken with that on the 22 human autosomes in order to test the hypothesis that reduction in repeat density in the avian genome has occurred as a result of adaptive evolution.The characteristics of repeat arrays on the 28 sequenced chicken chromosomes are summarized in Table In the chicken genome, there was a significant positive correlation  between chromosome length and the percentage of the chromosome occupied by repeats (% repeats) based on reassociation kinetics ,12. By c% based oMoreover, when simple sequence repeat array types shared between chicken and human genomes were compared, mean repeat array length and maximum repeat array length were significantly lower in the chicken than in human. The fact that these differences occurred consistently in nearly 300 distinct array types is evidence that the reduction in repeat arrays in the chicken has involved numerous independent evolutionary events. Mutational changes to simple sequence repeat arrays typically involve slippage events that either decrease or increase the number of repeat units . The facThere were substantial differences among chicken chromosomes with respect to the percentage of the chromosome occupied by repeats, and % repeats increased significantly as a function of chromosome length. This trend implies that the avian genome is characterized by an especially pronounced avoidance of longer repeats on the smaller chromosomes. This finding is consistent with the hypothesis of Burt  that theHowever, even the largest chicken chromosomes had repeat densities much lower than human chromosomes of similar length Figure . This imGallus gallus) genome assembly (May 2004 freeze, release 25.1b.1) was downloaded from Ensembl web site at . Only autosomes were used in the analyses; data were available for chromosomes 1 through 24, 26, 27, 28 and 32. We extracted Ensembl annotations of the features of repeat arrays (including repeat name, start and end positions on the chromosome, and orientation). The human genome assembly (May 2004 freeze, build 35 (hg17)) was downloaded via the UCSC Genome Browser . Repeat information based on the RepeatMasker annotations (repeat name, start and end positions on the chromosome and orientation) was extracted from the UCSC genome annotation database. Only autosomes (chromosomes 1 through 22) were used. For both chicken and human, repeats tallied included simple sequence repeats, class I elements, class II elements, low-complexity regions, and satellite regions. In addition, we compared between genomes a set of 294 simple sequence repeats which were present in both genomes; i.e., repeats of the same short nucleotide motif were present in both genomes. For these 294 repeat types, mean, minimum and maximum length of repeat arrays were compared in pairwise fashion between human and chicken.The chicken (HP gathered and summarized the data. ALH conducted statistical analyses and wrote the manuscript. Both authors read and approved the final manuscript.


Several problems exist with current methods used to align DNA sequences for comparative sequence analysis. Most dynamic programming algorithms assume that conserved sequence elements are collinear. This assumption appears valid when comparing orthologous protein coding sequences. Functional constraints on proteins provide strong selective pressure against sequence inversions, and minimize sequence duplications and feature shuffling. For non-coding sequences this collinearity assumption is often invalid. For example, enhancers contain clusters of transcription factor binding sites that change in number, orientation, and spacing during evolution yet the enhancer retains its activity. Dot plot analysis is often used to estimate non-coding sequence relatedness. Yet dot plots do not actually align sequences and thus cannot account well for base insertions or deletions. Moreover, they lack an adequate statistical framework for comparing sequence relatedness and are limited to pairwise comparisons. Lastly, dot plots and dynamic programming text outputs fail to provide an intuitive means for visualizing DNA alignments.). GATA uses the NCBI-BLASTN program and extensive post-processing to identify all small sub-alignments above a low cut-off score. These are graphed as two shaded boxes, one for each sequence, connected by a line using the coordinate system of their parent sequence. Shading and colour are used to indicate score and orientation. A variety of options exist for querying, modifying and retrieving conserved sequence elements. Extensive gene annotation can be added to both sequences using a standardized General Feature Format (GFF) file.To address some of these issues, we created a stand alone, platform independent, graphic alignment tool for comparative sequence analysis (GATA GATA uses the NCBI-BLASTN program in conjunction with post-processing to exhaustively align two DNA sequences. It provides researchers with a fine-grained alignment and visualization tool aptly suited for non-coding, 0–200 kb, pairwise, sequence analysis. It functions independent of sequence feature ordering or orientation, and readily visualizes both large and small sequence inversions, duplications, and segment shuffling. Since the alignment is visual and does not contain gaps, gene annotation can be added to both sequences to create a thoroughly descriptive picture of DNA conservation that is well suited for comparative sequence analysis. The most widely used methods for aligning DNA sequences rely on dynamic programming algorithms initially developed by Smith-Waterman and Needleman-Wunsch ,2. TheseWhen aligning protein coding sequences, dynamic programming works quite well. Evolution exerts significant functional constraint on protein coding sequences. When an inversion, duplication or segment-shuffling event occurs, the protein is often compromised by truncation due to the introduction of frame shifts and stop codons. These deleterious mutations are typically lost and not observed in the surviving population. When aligning this type of constrained sequence element, dynamic programming works quite well.Functional non-coding sequences do not appear to be as constrained in the ordering of elements as protein coding sequences -6. CompaGATA employs a two tiered architecture in aligning DNA sequences. GATAligner executes and processed BLASTN output. GATAPlotter displays the processed alignments and annotation from GATAligner.The GATAligner application figure  uses theOur initial goal was to create a high resolution sequence alignment and visualization tool to use in identifying small sequence rearrangements, like those associated with evolving non-coding regulatory DNA. We initially divided the first sequence into overlapping windows offset by one base pair. A Smith-Waterman dynamic programming algorithm was then used to align each window against the entire second sequence. Windows were scored, merged, and saved as above. Although this method is more rigorous than using BLASTN, it took 20–50 times as long, and did not produce significantly different results (data not shown). It should be noted that BLASTN requires seven consecutive identical bases to align two sequences. Thus in rare cases, some windows will be missed, for example, GGGGGGcTTTTTTaCCCCCCgAAAAAA versus GGGGGGaTTTTTTgCCCCCCtAAAAAA.The GATAPlotter application figure  takes suGATAPlotter also has the capability to display extensive gene annotation for one or both input sequences. The principle component of gene annotation rendering by GATA is the "GeneGroup" figure . Each GeDrosophila melanogaster and D. pseudoobscura. Figure To illustrate the types of rearrangements GATA can distinguish, examine figures Several related alignment and visualization tools have proven useful in comparative sequence analysis. Dot plot analysis can be used to identify duplications and inversions. Programs such as Dotter, JDotter, Dotlet, and Family Relations -16 generOne program that is proving quite useful in avoiding the collinearity problem while still using a dynamic programming algorithm is Shuffle LAGAN . AlignmeOne of the major challenges facing bioinformaticians is the development of alignment and visualization tools for multi-species comparative sequence analysis. Within the fly community alone, 12 divergent species of diptera and hymenoptera will be sequenced within 3 years. A variety of higher eukaryotes including human, mouse, rat, dog, chimp, cow, chicken, opossum, and platypus have or are in the process of being completely sequenced. How can one visualize the alignment and species-specific annotation for 12 orthologs of a particular gene or a genomic segment? The GATA alignment paradigm is well suited to this challenge and will play a prominent role in GATA's development.As comparative sequence analysis accelerates, scientists need more sophisticated alignment and visualization tools to define the evolutionary relationships and functional significance between particular orthologous sequences. This is especially true for regulatory, non-coding DNA that can show significant small-scale rearrangements. These new tools must incorporate detailed annotation alongside views of sequence conservation while providing easy access to the underlying sequence information. GATA provides one such solution.Project name:GATA, graphic alignment tool for comparative sequence analysis.Project home pages: and Operating system(s):Platform independentProgramming language:JavaOther requirements:Java 1.4 or higherLicense:GNU GPLAny restrictions to use by non-academics:NoneDAN designed and constructed the GATA programs with advice and supervision from MBE.


Dyslipidemia has been associated with hypertension. The present study explored if polymorphisms in genes encoding proteins in lipid metabolism could be used as predictors for the individual response to antihypertensive treatment.1-adrenergic receptor blocker atenolol for twelve weeks.Ten single nucleotide polymorphisms (SNP) in genes related to lipid metabolism were analysed by a microarray based minisequencing system in DNA samples from ninety-seven hypertensive subjects randomised to treatment with either 150 mg of the angiotensin II type 1 receptor blocker irbesartan or 50 mg of the βThe reduction in blood pressure was similar in both treatment groups. The SNP C711T in the apolipoprotein B gene was associated with the blood pressure response to irbesartan with an average reduction of 19 mmHg in the individuals carrying the C-allele, but not to atenolol. The C16730T polymorphism in the low density lipoprotein receptor gene predicted the change in systolic blood pressure in the atenolol group with an average reduction of 14 mmHg in the individuals carrying the C-allele.Polymorphisms in genes encoding proteins in the lipid metabolism are associated with the response to antihypertensive treatment in a drug specific pattern. These results highlight the potential use of pharmacogenetics as a guide for individualised antihypertensive treatment, and also the role of lipids in blood pressure control. Hypertension is a complex trait caused by multiple environmental and genetic factors interacting through the cardiac, vascular and endothelial systems. Several drug classes with different mechanisms of action, including inhibitors of the renin-angiotensin-aldosterone system (RAAS), calcium channel blockers, adrenergic receptor blockers and diuretics, are available for treatment of hypertension. However, the response to antihypertensive treatment is highly variable between individuals, which makes it difficult to predict the efficacy of a specific drug in the individual patient -3. CurreTwin studies have estimated that as much as half of the variability in blood pressure levels between individuals is due to genetic factors ,8. Based1-adrenergic receptor blocker atenolol [The RAAS and the sympathetic nervous system play key roles in blood pressure regulation. We have earlier shown that polymorphisms in the angiotensin converting enzyme gene  and a SNatenolol . DyslipiWe have recently developed a microarray based minisequencing system for parallel genotyping of multiple SNPs in blood pressure regulating candidate genes . Here we1-adrenergic receptor blocker atenolol once daily as monotherapy. The dose was doubled after six weeks if the diastolic blood pressure was ≥ 90 mmHg. Blood pressure was measured by trained nurses using a mercury sphygmomanometer, after the patients had rested for at least 10 min in the seated position. Left ventricular hypertrophy was defined as left ventricular mass index of > 131 g/m2 for men and > 100 g/m2 for women, assessed by echocardiography. The data presented relates to the change in blood pressure after 12 weeks of treatment. For details on the SILVHIA trial, see Malmqvist etal [DNA extracted from blood samples from 97 hypertensive patients from the double blind parallel group "Swedish Irbesartan Left Ventricular Hypertrophy Investigation versus Atenolol" (SILVHIA) trial  were anaist etal . Baselin) and the SNP Consortium (TSC, ) databases and validated in a pooled DNA sample representing the Swedish population. A subset of these SNPs located in genes involved in lipid metabolism and that were polymorphic in the Swedish population were included in the study presented here, together with one additional SNP in the apolipoprotein A-V gene. See Table In our previous study , 98 SNPsFragments comprising the SNPs were amplified in multiplex PCR described previously . A microAnalysis of covariance (ANCOVA) with each SNP as factor, baseline blood pressure as covariate and the change in blood pressure as response, was performed. The analyses were performed by treatment group and blood pressure measurement (systolic and diastolic blood pressures). Correction for multiple testing was performed by calculation of critical p-values corresponding to a nominal type I error of 5% using a permutation test . Two taiWe explored possible associations between individual genotypes of ten SNPs and reduction in systolic and diastolic blood pressure as response to treatment with atenolol or irbesartan Figure  in samplCorrection for multiple testing using a permutation test  yielded The SNP C711T in the apolipoprotein B gene is located in the coding region of the gene, and alters a threonine residue to an isoleucine residue in the protein. This SNP is located in the amino-terminal part of the enzyme and has been suggested to affect the dimerisation of apolipoprotein B and low density lipoprotein during cholesterol transport . The C16We have recently found circulating apolipoprotein B to be the most powerful predictor of endothelium-dependent vasodilation of the commonly used markers of cholesterol metabolism . It is nIn our earlier exploratory study, 74 SNPs with a minor allele frequency over 5%, including nine of the SNPs analysed here were tested as predictors of blood pressure regulation in the SILVHIA study samples using a multiple regression model . The maiA remaining weakness in our study is the small number of samples available for analysis, which does not allow detection of small to medium size gene effects, and results in uncertain estimation of the the magnitude of the effects detected. Moreover, in a small study there is the risk of a non-representative group of patients with respect to gender, age, and genotype distribution. Despite these limitations, we detected a significant effect of the SNP C711T in the apolipoprotein B gene and the SNP C16730T in the low density lipoprotein receptor after correction for multiple testing. The pharmacogenetically interesting results from our study need to be replicated in other studies.As the C711T SNP in the apolipoprotein B gene predicted response to treatment with irbesartan, and the C16730T SNP in the low density lipoprotein receptor gene appeared to predict response to atenolol treatment, our results point at possible use of SNPs in genes encoding components of lipid metabolism in pharmacogenetic panels for selecting the optimal drug for each patient. To our knowledge our study is the first one to investigate the relationship between polymorphisms in genes involved in lipid metabolism and the response to antihypertensive treatment.The authors declare that they have no competing interests.UL performed the development of genotyping technology, genotyping lab work, interpretation of data and had a substantial role in writing the manuscript. LL provided clinical expertise, participated in selection of candidate genes and contributed to writing. LK provided clinical expertise, established a database of the SILVHIA phenotypes, and in writing. LB performed the statistical analysis. TK provided the SILVHIA samples and contributed to writing the manuscript. A-CS contributed by planning and supervision of the project, and to writing the manuscript.The pre-publication history for this paper can be accessed here: